diff --git a/algorithms-miscellaneous-3/pom.xml b/algorithms-miscellaneous-3/pom.xml
index 1e5ba6650a..888f8e2e2c 100644
--- a/algorithms-miscellaneous-3/pom.xml
+++ b/algorithms-miscellaneous-3/pom.xml
@@ -1,5 +1,5 @@
+ xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
4.0.0
algorithms-miscellaneous-3
0.0.1-SNAPSHOT
@@ -18,29 +18,29 @@
${org.assertj.core.version}
test
-
+
- org.apache.commons
- commons-collections4
- ${commons-collections4.version}
-
-
-
- com.google.guava
- guava
- ${guava.version}
+ org.apache.commons
+ commons-collections4
+ ${commons-collections4.version}
-
- com.squareup.retrofit2
- retrofit
- ${retrofit.version}
-
-
- com.squareup.retrofit2
- converter-jackson
- ${retrofit.version}
-
+
+ com.google.guava
+ guava
+ ${guava.version}
+
+
+
+ com.squareup.retrofit2
+ retrofit
+ ${retrofit.version}
+
+
+ com.squareup.retrofit2
+ converter-jackson
+ ${retrofit.version}
+
@@ -59,6 +59,6 @@
3.9.0
4.3
28.0-jre
- 2.6.0
+ 2.6.0
\ No newline at end of file
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Centroid.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Centroid.java
index 9f3aca7916..462936541b 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Centroid.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Centroid.java
@@ -8,34 +8,34 @@ import java.util.Objects;
*/
public class Centroid {
- /**
- * The centroid coordinates.
- */
- private final Map coordinates;
+ /**
+ * The centroid coordinates.
+ */
+ private final Map coordinates;
- public Centroid(Map coordinates) {
- this.coordinates = coordinates;
- }
+ public Centroid(Map coordinates) {
+ this.coordinates = coordinates;
+ }
- public Map getCoordinates() {
- return coordinates;
- }
+ public Map getCoordinates() {
+ return coordinates;
+ }
- @Override
- public boolean equals(Object o) {
- if (this == o) return true;
- if (o == null || getClass() != o.getClass()) return false;
- Centroid centroid = (Centroid) o;
- return Objects.equals(getCoordinates(), centroid.getCoordinates());
- }
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) return true;
+ if (o == null || getClass() != o.getClass()) return false;
+ Centroid centroid = (Centroid) o;
+ return Objects.equals(getCoordinates(), centroid.getCoordinates());
+ }
- @Override
- public int hashCode() {
- return Objects.hash(getCoordinates());
- }
+ @Override
+ public int hashCode() {
+ return Objects.hash(getCoordinates());
+ }
- @Override
- public String toString() {
- return "Centroid " + coordinates;
- }
+ @Override
+ public String toString() {
+ return "Centroid " + coordinates;
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Distance.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Distance.java
index 103eedb732..30723cb6b3 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Distance.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Distance.java
@@ -8,13 +8,13 @@ import java.util.Map;
*/
public interface Distance {
- /**
- * Calculates the distance between two feature vectors.
- *
- * @param f1 The first set of features.
- * @param f2 The second set of features.
- * @return Calculated distance.
- * @throws IllegalArgumentException If the given feature vectors are invalid.
- */
- double calculate(Map f1, Map f2);
+ /**
+ * Calculates the distance between two feature vectors.
+ *
+ * @param f1 The first set of features.
+ * @param f2 The second set of features.
+ * @return Calculated distance.
+ * @throws IllegalArgumentException If the given feature vectors are invalid.
+ */
+ double calculate(Map f1, Map f2);
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Errors.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Errors.java
index 0fbe24c5ad..3228876051 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Errors.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Errors.java
@@ -8,16 +8,16 @@ import java.util.Map;
*/
public class Errors {
- public static double sse(Map> clustered, Distance distance) {
- double sum = 0;
- for (Map.Entry> entry : clustered.entrySet()) {
- Centroid centroid = entry.getKey();
- for (Record record : entry.getValue()) {
- double d = distance.calculate(centroid.getCoordinates(), record.getFeatures());
- sum += Math.pow(d, 2);
- }
- }
+ public static double sse(Map> clustered, Distance distance) {
+ double sum = 0;
+ for (Map.Entry> entry : clustered.entrySet()) {
+ Centroid centroid = entry.getKey();
+ for (Record record : entry.getValue()) {
+ double d = distance.calculate(centroid.getCoordinates(), record.getFeatures());
+ sum += Math.pow(d, 2);
+ }
+ }
- return sum;
- }
+ return sum;
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/EuclideanDistance.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/EuclideanDistance.java
index 62d24feedf..faccd97599 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/EuclideanDistance.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/EuclideanDistance.java
@@ -7,19 +7,18 @@ import java.util.Map;
*/
public class EuclideanDistance implements Distance {
- @Override
- public double calculate(Map f1, Map f2) {
- if (f1 == null || f2 == null)
- throw new IllegalArgumentException("Feature vectors can't be null");
+ @Override
+ public double calculate(Map f1, Map f2) {
+ if (f1 == null || f2 == null) throw new IllegalArgumentException("Feature vectors can't be null");
- double sum = 0;
- for (String key : f1.keySet()) {
- Double v1 = f1.get(key);
- Double v2 = f2.get(key);
+ double sum = 0;
+ for (String key : f1.keySet()) {
+ Double v1 = f1.get(key);
+ Double v2 = f2.get(key);
- if (v1 != null && v2 != null) sum += Math.pow(v1 - v2, 2);
- }
+ if (v1 != null && v2 != null) sum += Math.pow(v1 - v2, 2);
+ }
- return Math.sqrt(sum);
- }
+ return Math.sqrt(sum);
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/KMeans.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/KMeans.java
index d8ab70b0fd..e1152a67d6 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/KMeans.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/KMeans.java
@@ -17,200 +17,208 @@ import static java.util.stream.Collectors.toSet;
*/
public class KMeans {
- private KMeans() {
- throw new IllegalAccessError("You shouldn't call this constructor");
- }
+ private KMeans() {
+ throw new IllegalAccessError("You shouldn't call this constructor");
+ }
- /**
- * Will be used to generate random numbers.
- */
- private static final Random random = new Random();
+ /**
+ * Will be used to generate random numbers.
+ */
+ private static final Random random = new Random();
- /**
- * Performs the K-Means clustering algorithm on the given dataset.
- *
- * @param records The dataset.
- * @param k Number of Clusters.
- * @param distance To calculate the distance between two items.
- * @param maxIterations Upper bound for the number of iterations.
- * @return K clusters along with their features.
- */
- public static Map> fit(List records, int k, Distance distance, int maxIterations) {
- applyPreconditions(records, k, distance, maxIterations);
+ /**
+ * Performs the K-Means clustering algorithm on the given dataset.
+ *
+ * @param records The dataset.
+ * @param k Number of Clusters.
+ * @param distance To calculate the distance between two items.
+ * @param maxIterations Upper bound for the number of iterations.
+ * @return K clusters along with their features.
+ */
+ public static Map> fit(List records, int k, Distance distance, int maxIterations) {
+ applyPreconditions(records, k, distance, maxIterations);
- List centroids = randomCentroids(records, k);
- Map> clusters = new HashMap<>();
- Map> lastState = new HashMap<>();
+ List centroids = randomCentroids(records, k);
+ Map> clusters = new HashMap<>();
+ Map> lastState = new HashMap<>();
- // iterate for a pre-defined number of times
- for (int i = 0; i < maxIterations; i++) {
- boolean isLastIteration = i == maxIterations - 1;
+ // iterate for a pre-defined number of times
+ for (int i = 0; i < maxIterations; i++) {
+ boolean isLastIteration = i == maxIterations - 1;
- // in each iteration we should find the nearest centroid for each record
- for (Record record : records) {
- Centroid centroid = nearestCentroid(record, centroids, distance);
- assignToCluster(clusters, record, centroid);
- }
+ // in each iteration we should find the nearest centroid for each record
+ for (Record record : records) {
+ Centroid centroid = nearestCentroid(record, centroids, distance);
+ assignToCluster(clusters, record, centroid);
+ }
- // if the assignment does not change, then the algorithm terminates
- boolean shouldTerminate = isLastIteration || clusters.equals(lastState);
- lastState = clusters;
- if (shouldTerminate) break;
+ // if the assignment does not change, then the algorithm terminates
+ boolean shouldTerminate = isLastIteration || clusters.equals(lastState);
+ lastState = clusters;
+ if (shouldTerminate) break;
- // at the end of each iteration we should relocate the centroids
- centroids = relocateCentroids(clusters);
- clusters = new HashMap<>();
- }
+ // at the end of each iteration we should relocate the centroids
+ centroids = relocateCentroids(clusters);
+ clusters = new HashMap<>();
+ }
- return lastState;
- }
+ return lastState;
+ }
- /**
- * Move all cluster centroids to the average of all assigned features.
- *
- * @param clusters The current cluster configuration.
- * @return Collection of new and relocated centroids.
- */
- private static List relocateCentroids(Map> clusters) {
- return clusters.entrySet().stream()
- .map(e -> average(e.getKey(), e.getValue())).collect(toList());
- }
+ /**
+ * Move all cluster centroids to the average of all assigned features.
+ *
+ * @param clusters The current cluster configuration.
+ * @return Collection of new and relocated centroids.
+ */
+ private static List relocateCentroids(Map> clusters) {
+ return clusters
+ .entrySet()
+ .stream()
+ .map(e -> average(e.getKey(), e.getValue()))
+ .collect(toList());
+ }
- /**
- * Moves the given centroid to the average position of all assigned features. If
- * the centroid has no feature in its cluster, then there would be no need for a
- * relocation. Otherwise, for each entry we calculate the average of all records
- * first by summing all the entries and then dividing the final summation value by
- * the number of records.
- *
- * @param centroid The centroid to move.
- * @param records The assigned features.
- * @return The moved centroid.
- */
- private static Centroid average(Centroid centroid, List records) {
- // if this cluster is empty, then we shouldn't move the centroid
- if (records == null || records.isEmpty()) return centroid;
+ /**
+ * Moves the given centroid to the average position of all assigned features. If
+ * the centroid has no feature in its cluster, then there would be no need for a
+ * relocation. Otherwise, for each entry we calculate the average of all records
+ * first by summing all the entries and then dividing the final summation value by
+ * the number of records.
+ *
+ * @param centroid The centroid to move.
+ * @param records The assigned features.
+ * @return The moved centroid.
+ */
+ private static Centroid average(Centroid centroid, List records) {
+ // if this cluster is empty, then we shouldn't move the centroid
+ if (records == null || records.isEmpty()) return centroid;
- // Since some records don't have all possible attributes, we initialize
- // average coordinates equal to current centroid coordinates
- Map average = centroid.getCoordinates();
+ // Since some records don't have all possible attributes, we initialize
+ // average coordinates equal to current centroid coordinates
+ Map average = centroid.getCoordinates();
- // The average function works correctly if we clear all coordinates corresponding
- // to present record attributes
- records.stream().flatMap(e -> e.getFeatures().keySet().stream())
- .forEach(k -> average.put(k, 0.0));
+ // The average function works correctly if we clear all coordinates corresponding
+ // to present record attributes
+ records
+ .stream()
+ .flatMap(e -> e
+ .getFeatures()
+ .keySet()
+ .stream())
+ .forEach(k -> average.put(k, 0.0));
- for (Record record : records) {
- record.getFeatures().forEach(
- (k, v) -> average.compute(k, (k1, currentValue) -> v + currentValue)
- );
- }
+ for (Record record : records) {
+ record
+ .getFeatures()
+ .forEach((k, v) -> average.compute(k, (k1, currentValue) -> v + currentValue));
+ }
- average.forEach((k, v) -> average.put(k, v / records.size()));
+ average.forEach((k, v) -> average.put(k, v / records.size()));
- return new Centroid(average);
- }
+ return new Centroid(average);
+ }
- /**
- * Assigns a feature vector to the given centroid. If this is the first assignment for this centroid,
- * first we should create the list.
- *
- * @param clusters The current cluster configuration.
- * @param record The feature vector.
- * @param centroid The centroid.
- */
- private static void assignToCluster(Map> clusters,
- Record record, Centroid centroid) {
- clusters.compute(centroid, (key, list) -> {
- if (list == null) {
- list = new ArrayList<>();
- }
+ /**
+ * Assigns a feature vector to the given centroid. If this is the first assignment for this centroid,
+ * first we should create the list.
+ *
+ * @param clusters The current cluster configuration.
+ * @param record The feature vector.
+ * @param centroid The centroid.
+ */
+ private static void assignToCluster(Map> clusters, Record record, Centroid centroid) {
+ clusters.compute(centroid, (key, list) -> {
+ if (list == null) {
+ list = new ArrayList<>();
+ }
- list.add(record);
- return list;
- });
- }
+ list.add(record);
+ return list;
+ });
+ }
- /**
- * With the help of the given distance calculator, iterates through centroids and finds the
- * nearest one to the given record.
- *
- * @param record The feature vector to find a centroid for.
- * @param centroids Collection of all centroids.
- * @param distance To calculate the distance between two items.
- * @return The nearest centroid to the given feature vector.
- */
- private static Centroid nearestCentroid(Record record, List centroids,
- Distance distance) {
- double minimumDistance = Double.MAX_VALUE;
- Centroid nearest = null;
+ /**
+ * With the help of the given distance calculator, iterates through centroids and finds the
+ * nearest one to the given record.
+ *
+ * @param record The feature vector to find a centroid for.
+ * @param centroids Collection of all centroids.
+ * @param distance To calculate the distance between two items.
+ * @return The nearest centroid to the given feature vector.
+ */
+ private static Centroid nearestCentroid(Record record, List centroids, Distance distance) {
+ double minimumDistance = Double.MAX_VALUE;
+ Centroid nearest = null;
- for (Centroid centroid : centroids) {
- double currentDistance = distance.calculate(record.getFeatures(), centroid.getCoordinates());
+ for (Centroid centroid : centroids) {
+ double currentDistance = distance.calculate(record.getFeatures(), centroid.getCoordinates());
- if (currentDistance < minimumDistance) {
- minimumDistance = currentDistance;
- nearest = centroid;
- }
- }
+ if (currentDistance < minimumDistance) {
+ minimumDistance = currentDistance;
+ nearest = centroid;
+ }
+ }
- return nearest;
- }
+ return nearest;
+ }
- /**
- * Generates k random centroids. Before kicking-off the centroid generation process,
- * first we calculate the possible value range for each attribute. Then when
- * we're going to generate the centroids, we generate random coordinates in
- * the [min, max] range for each attribute.
- *
- * @param records The dataset which helps to calculate the [min, max] range for
- * each attribute.
- * @param k Number of clusters.
- * @return Collections of randomly generated centroids.
- */
- private static List randomCentroids(List records, int k) {
- List centroids = new ArrayList<>();
- Map maxs = new HashMap<>();
- Map mins = new HashMap<>();
+ /**
+ * Generates k random centroids. Before kicking-off the centroid generation process,
+ * first we calculate the possible value range for each attribute. Then when
+ * we're going to generate the centroids, we generate random coordinates in
+ * the [min, max] range for each attribute.
+ *
+ * @param records The dataset which helps to calculate the [min, max] range for
+ * each attribute.
+ * @param k Number of clusters.
+ * @return Collections of randomly generated centroids.
+ */
+ private static List randomCentroids(List records, int k) {
+ List centroids = new ArrayList<>();
+ Map maxs = new HashMap<>();
+ Map mins = new HashMap<>();
- for (Record record : records) {
- record.getFeatures().forEach((key, value) -> {
- // compares the value with the current max and choose the bigger value between them
- maxs.compute(key, (k1, max) -> max == null || value > max ? value : max);
+ for (Record record : records) {
+ record
+ .getFeatures()
+ .forEach((key, value) -> {
+ // compares the value with the current max and choose the bigger value between them
+ maxs.compute(key, (k1, max) -> max == null || value > max ? value : max);
- // compare the value with the current min and choose the smaller value between them
- mins.compute(key, (k1, min) -> min == null || value < min ? value : min);
- });
- }
+ // compare the value with the current min and choose the smaller value between them
+ mins.compute(key, (k1, min) -> min == null || value < min ? value : min);
+ });
+ }
- Set attributes = records.stream()
- .flatMap(e -> e.getFeatures().keySet().stream()).collect(toSet());
- for (int i = 0; i < k; i++) {
- Map coordinates = new HashMap<>();
- for (String attribute : attributes) {
- double max = maxs.get(attribute);
- double min = mins.get(attribute);
- coordinates.put(attribute, random.nextDouble() * (max - min) + min);
- }
+ Set attributes = records
+ .stream()
+ .flatMap(e -> e
+ .getFeatures()
+ .keySet()
+ .stream())
+ .collect(toSet());
+ for (int i = 0; i < k; i++) {
+ Map coordinates = new HashMap<>();
+ for (String attribute : attributes) {
+ double max = maxs.get(attribute);
+ double min = mins.get(attribute);
+ coordinates.put(attribute, random.nextDouble() * (max - min) + min);
+ }
- centroids.add(new Centroid(coordinates));
- }
+ centroids.add(new Centroid(coordinates));
+ }
- return centroids;
- }
+ return centroids;
+ }
- private static void applyPreconditions(List records, int k,
- Distance distance, int maxIterations) {
- if (records == null || records.isEmpty())
- throw new IllegalArgumentException("The dataset can't be empty");
+ private static void applyPreconditions(List records, int k, Distance distance, int maxIterations) {
+ if (records == null || records.isEmpty()) throw new IllegalArgumentException("The dataset can't be empty");
- if (k <= 1)
- throw new IllegalArgumentException("It doesn't make sense to have less than or equal to 1 cluster");
+ if (k <= 1) throw new IllegalArgumentException("It doesn't make sense to have less than or equal to 1 cluster");
- if (distance == null)
- throw new IllegalArgumentException("The distance calculator is required");
+ if (distance == null) throw new IllegalArgumentException("The distance calculator is required");
- if (maxIterations <= 0)
- throw new IllegalArgumentException("Max iterations should be a positive number");
- }
+ if (maxIterations <= 0) throw new IllegalArgumentException("Max iterations should be a positive number");
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFm.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFm.java
index 7d241d3a79..4694a845af 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFm.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFm.java
@@ -19,101 +19,126 @@ import static java.util.stream.Collectors.toSet;
public class LastFm {
- private static OkHttpClient okHttp = new OkHttpClient.Builder()
- .addInterceptor(new LastFmService.Authenticator("put your API key here"))
- .build();
+ private static OkHttpClient okHttp = new OkHttpClient.Builder()
+ .addInterceptor(new LastFmService.Authenticator("put your API key here"))
+ .build();
- private static Retrofit retrofit = new Retrofit.Builder().client(okHttp)
- .addConverterFactory(JacksonConverterFactory.create())
- .baseUrl("http://ws.audioscrobbler.com/")
- .build();
+ private static Retrofit retrofit = new Retrofit.Builder()
+ .client(okHttp)
+ .addConverterFactory(JacksonConverterFactory.create())
+ .baseUrl("http://ws.audioscrobbler.com/")
+ .build();
- private static LastFmService lastFm = retrofit.create(LastFmService.class);
+ private static LastFmService lastFm = retrofit.create(LastFmService.class);
- private static ObjectMapper mapper = new ObjectMapper();
+ private static ObjectMapper mapper = new ObjectMapper();
- public static void main(String[] args) throws IOException {
- List artists = getTop100Artists();
- Set tags = getTop100Tags();
- List records = datasetWithTaggedArtists(artists, tags);
+ public static void main(String[] args) throws IOException {
+ List artists = getTop100Artists();
+ Set tags = getTop100Tags();
+ List records = datasetWithTaggedArtists(artists, tags);
- Map> clusters = KMeans.fit(records, 7, new EuclideanDistance(), 1000);
- // Print the cluster configuration
- clusters.forEach((key, value) -> {
- System.out.println("------------------------------ CLUSTER -----------------------------------");
+ Map> clusters = KMeans.fit(records, 7, new EuclideanDistance(), 1000);
+ // Print the cluster configuration
+ clusters.forEach((key, value) -> {
+ System.out.println("------------------------------ CLUSTER -----------------------------------");
- System.out.println(sortedCentroid(key));
- String members = String.join(", ", value.stream().map(Record::getDescription).collect(toSet()));
- System.out.print(members);
+ System.out.println(sortedCentroid(key));
+ String members = String.join(", ", value
+ .stream()
+ .map(Record::getDescription)
+ .collect(toSet()));
+ System.out.print(members);
- System.out.println();
- System.out.println();
- });
+ System.out.println();
+ System.out.println();
+ });
- Map json = convertToD3CompatibleMap(clusters);
- System.out.println(mapper.writeValueAsString(json));
- }
+ Map json = convertToD3CompatibleMap(clusters);
+ System.out.println(mapper.writeValueAsString(json));
+ }
- private static Map convertToD3CompatibleMap(Map> clusters) {
- Map json = new HashMap<>();
- json.put("name", "Musicians");
- List> children = new ArrayList<>();
- clusters.forEach((key, value) -> {
- Map child = new HashMap<>();
- child.put("name", dominantGenre(sortedCentroid(key)));
- List> nested = new ArrayList<>();
- for (Record record : value) {
- nested.add(Collections.singletonMap("name", record.getDescription()));
- }
- child.put("children", nested);
+ private static Map convertToD3CompatibleMap(Map> clusters) {
+ Map json = new HashMap<>();
+ json.put("name", "Musicians");
+ List> children = new ArrayList<>();
+ clusters.forEach((key, value) -> {
+ Map child = new HashMap<>();
+ child.put("name", dominantGenre(sortedCentroid(key)));
+ List> nested = new ArrayList<>();
+ for (Record record : value) {
+ nested.add(Collections.singletonMap("name", record.getDescription()));
+ }
+ child.put("children", nested);
+ children.add(child);
+ });
+ json.put("children", children);
+ return json;
+ }
- children.add(child);
- });
- json.put("children", children);
- return json;
- }
+ private static String dominantGenre(Centroid centroid) {
+ return centroid
+ .getCoordinates()
+ .keySet()
+ .stream()
+ .limit(2)
+ .collect(Collectors.joining(", "));
+ }
- private static String dominantGenre(Centroid centroid) {
- return centroid.getCoordinates().keySet().stream().limit(2).collect(Collectors.joining(", "));
- }
+ private static Centroid sortedCentroid(Centroid key) {
+ List> entries = new ArrayList<>(key
+ .getCoordinates()
+ .entrySet());
+ entries.sort((e1, e2) -> e2
+ .getValue()
+ .compareTo(e1.getValue()));
- private static Centroid sortedCentroid(Centroid key) {
- List> entries = new ArrayList<>(key.getCoordinates().entrySet());
- entries.sort((e1, e2) -> e2.getValue().compareTo(e1.getValue()));
+ Map sorted = new LinkedHashMap<>();
+ for (Map.Entry entry : entries) {
+ sorted.put(entry.getKey(), entry.getValue());
+ }
- Map sorted = new LinkedHashMap<>();
- for (Map.Entry entry : entries) {
- sorted.put(entry.getKey(), entry.getValue());
- }
+ return new Centroid(sorted);
+ }
- return new Centroid(sorted);
- }
+ private static List datasetWithTaggedArtists(List artists, Set topTags) throws IOException {
+ List records = new ArrayList<>();
+ for (String artist : artists) {
+ Map tags = lastFm
+ .topTagsFor(artist)
+ .execute()
+ .body()
+ .all();
- private static List datasetWithTaggedArtists(List artists,
- Set topTags) throws IOException {
- List records = new ArrayList<>();
- for (String artist : artists) {
- Map tags = lastFm.topTagsFor(artist).execute().body().all();
+ // Only keep popular tags.
+ tags
+ .entrySet()
+ .removeIf(e -> !topTags.contains(e.getKey()));
- // Only keep popular tags.
- tags.entrySet().removeIf(e -> !topTags.contains(e.getKey()));
+ records.add(new Record(artist, tags));
+ }
+ return records;
+ }
- records.add(new Record(artist, tags));
- }
- return records;
- }
+ private static Set getTop100Tags() throws IOException {
+ return lastFm
+ .topTags()
+ .execute()
+ .body()
+ .all();
+ }
- private static Set getTop100Tags() throws IOException {
- return lastFm.topTags().execute().body().all();
- }
+ private static List getTop100Artists() throws IOException {
+ List artists = new ArrayList<>();
+ for (int i = 1; i <= 2; i++) {
+ artists.addAll(lastFm
+ .topArtists(i)
+ .execute()
+ .body()
+ .all());
+ }
- private static List getTop100Artists() throws IOException {
- List artists = new ArrayList<>();
- for (int i = 1; i <= 2; i++) {
- artists.addAll(lastFm.topArtists(i).execute().body().all());
- }
-
- return artists;
- }
+ return artists;
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFmService.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFmService.java
index cfc8e8d478..db57deb888 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFmService.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/LastFmService.java
@@ -23,84 +23,96 @@ import static java.util.stream.Collectors.toList;
public interface LastFmService {
- @GET("/2.0/?method=chart.gettopartists&format=json&limit=50")
- Call topArtists(@Query("page") int page);
+ @GET("/2.0/?method=chart.gettopartists&format=json&limit=50")
+ Call topArtists(@Query("page") int page);
- @GET("/2.0/?method=artist.gettoptags&format=json&limit=20&autocorrect=1")
- Call topTagsFor(@Query("artist") String artist);
+ @GET("/2.0/?method=artist.gettoptags&format=json&limit=20&autocorrect=1")
+ Call topTagsFor(@Query("artist") String artist);
- @GET("/2.0/?method=chart.gettoptags&format=json&limit=100")
- Call topTags();
+ @GET("/2.0/?method=chart.gettoptags&format=json&limit=100")
+ Call topTags();
- /**
- * HTTP interceptor to intercept all HTTP requests and add the API key to them.
- */
- class Authenticator implements Interceptor {
+ /**
+ * HTTP interceptor to intercept all HTTP requests and add the API key to them.
+ */
+ class Authenticator implements Interceptor {
- private final String apiKey;
+ private final String apiKey;
- Authenticator(String apiKey) {
- this.apiKey = apiKey;
- }
+ Authenticator(String apiKey) {
+ this.apiKey = apiKey;
+ }
- @Override
- public Response intercept(Chain chain) throws IOException {
- HttpUrl url = chain.request().url().newBuilder().addQueryParameter("api_key", apiKey).build();
- Request request = chain.request().newBuilder().url(url).build();
+ @Override
+ public Response intercept(Chain chain) throws IOException {
+ HttpUrl url = chain
+ .request()
+ .url()
+ .newBuilder()
+ .addQueryParameter("api_key", apiKey)
+ .build();
+ Request request = chain
+ .request()
+ .newBuilder()
+ .url(url)
+ .build();
- return chain.proceed(request);
- }
- }
+ return chain.proceed(request);
+ }
+ }
- @JsonAutoDetect(fieldVisibility = ANY)
- class TopTags {
+ @JsonAutoDetect(fieldVisibility = ANY)
+ class TopTags {
- private Map tags;
+ private Map tags;
- @SuppressWarnings("unchecked")
- public Set all() {
- List> topTags = (List>) tags.get("tag");
- return topTags.stream().map(e -> ((String) e.get("name"))).collect(Collectors.toSet());
- }
- }
+ @SuppressWarnings("unchecked")
+ public Set all() {
+ List> topTags = (List>) tags.get("tag");
+ return topTags
+ .stream()
+ .map(e -> ((String) e.get("name")))
+ .collect(Collectors.toSet());
+ }
+ }
- @JsonAutoDetect(fieldVisibility = ANY)
- class Tags {
+ @JsonAutoDetect(fieldVisibility = ANY)
+ class Tags {
- @JsonProperty("toptags")
- private Map topTags;
+ @JsonProperty("toptags") private Map topTags;
- @SuppressWarnings("unchecked")
- public Map all() {
- try {
- Map all = new HashMap<>();
- List> tags = (List>) topTags.get("tag");
- for (Map tag : tags) {
- all.put(((String) tag.get("name")), ((Integer) tag.get("count")).doubleValue());
- }
+ @SuppressWarnings("unchecked")
+ public Map all() {
+ try {
+ Map all = new HashMap<>();
+ List> tags = (List>) topTags.get("tag");
+ for (Map tag : tags) {
+ all.put(((String) tag.get("name")), ((Integer) tag.get("count")).doubleValue());
+ }
- return all;
- }
- catch (Exception e) {
- return Collections.emptyMap();
- }
- }
- }
+ return all;
+ } catch (Exception e) {
+ return Collections.emptyMap();
+ }
+ }
+ }
- @JsonAutoDetect(fieldVisibility = ANY)
- class Artists {
+ @JsonAutoDetect(fieldVisibility = ANY)
+ class Artists {
- private Map artists;
+ private Map artists;
- @SuppressWarnings("unchecked")
- public List all() {
- try {
- List> artists = (List>) this.artists.get("artist");
- return artists.stream().map(e -> ((String) e.get("name"))).collect(toList());
- }
- catch (Exception e) {
- return Collections.emptyList();
- }
- }
- }
+ @SuppressWarnings("unchecked")
+ public List all() {
+ try {
+ List> artists = (List>) this.artists.get("artist");
+ return artists
+ .stream()
+ .map(e -> ((String) e.get("name")))
+ .collect(toList());
+ } catch (Exception e) {
+ return Collections.emptyList();
+ }
+ }
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Record.java b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Record.java
index 6aa2c3ba90..a29e3e054b 100644
--- a/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Record.java
+++ b/algorithms-miscellaneous-3/src/main/java/com/baeldung/algorithms/kmeans/Record.java
@@ -9,52 +9,53 @@ import java.util.Objects;
*/
public class Record {
- /**
- * The record description. For example, this can be the artist name for the famous musician
- * example.
- */
- private final String description;
+ /**
+ * The record description. For example, this can be the artist name for the famous musician
+ * example.
+ */
+ private final String description;
- /**
- * Encapsulates all attributes and their corresponding values, i.e. features.
- */
- private final Map features;
+ /**
+ * Encapsulates all attributes and their corresponding values, i.e. features.
+ */
+ private final Map features;
- public Record(String description, Map features) {
- this.description = description;
- this.features = features;
- }
+ public Record(String description, Map features) {
+ this.description = description;
+ this.features = features;
+ }
- public Record(Map features) {
- this("", features);
- }
+ public Record(Map features) {
+ this("", features);
+ }
- public String getDescription() {
- return description;
- }
+ public String getDescription() {
+ return description;
+ }
- public Map getFeatures() {
- return features;
- }
+ public Map getFeatures() {
+ return features;
+ }
- @Override
- public String toString() {
- String prefix = description == null || description.trim().isEmpty() ? "Record" : description;
+ @Override
+ public String toString() {
+ String prefix = description == null || description
+ .trim()
+ .isEmpty() ? "Record" : description;
- return prefix + ": " + features;
- }
+ return prefix + ": " + features;
+ }
- @Override
- public boolean equals(Object o) {
- if (this == o) return true;
- if (o == null || getClass() != o.getClass()) return false;
- Record record = (Record) o;
- return Objects.equals(getDescription(), record.getDescription()) &&
- Objects.equals(getFeatures(), record.getFeatures());
- }
+ @Override
+ public boolean equals(Object o) {
+ if (this == o) return true;
+ if (o == null || getClass() != o.getClass()) return false;
+ Record record = (Record) o;
+ return Objects.equals(getDescription(), record.getDescription()) && Objects.equals(getFeatures(), record.getFeatures());
+ }
- @Override
- public int hashCode() {
- return Objects.hash(getDescription(), getFeatures());
- }
+ @Override
+ public int hashCode() {
+ return Objects.hash(getDescription(), getFeatures());
+ }
}
diff --git a/algorithms-miscellaneous-3/src/main/resources/kmeans/radial.html b/algorithms-miscellaneous-3/src/main/resources/kmeans/radial.html
index d7f9b74cbc..e7e7403871 100644
--- a/algorithms-miscellaneous-3/src/main/resources/kmeans/radial.html
+++ b/algorithms-miscellaneous-3/src/main/resources/kmeans/radial.html
@@ -6,9 +6,11 @@
stroke: steelblue;
stroke-width: 1.5px;
}
+
.node {
font: 10px sans-serif;
}
+
.link {
fill: none;
stroke: #ccc;
@@ -21,15 +23,19 @@
var diameter = 1100;
var tree = d3.layout.tree()
.size([360, diameter / 2 - 300])
- .separation(function(a, b) { return (a.parent == b.parent ? 1 : 2) / a.depth; });
+ .separation(function (a, b) {
+ return (a.parent == b.parent ? 1 : 2) / a.depth;
+ });
var diagonal = d3.svg.diagonal.radial()
- .projection(function(d) { return [d.y, d.x / 180 * Math.PI]; });
+ .projection(function (d) {
+ return [d.y, d.x / 180 * Math.PI];
+ });
var svg = d3.select("body").append("svg")
.attr("width", diameter)
.attr("height", diameter - 150)
.append("g")
.attr("transform", "translate(" + diameter / 2 + "," + diameter / 2 + ")");
- d3.json("lastfm.json", function(error, root) {
+ d3.json("lastfm.json", function (error, root) {
var nodes = tree.nodes(root),
links = tree.links(nodes);
var link = svg.selectAll(".link")
@@ -41,14 +47,22 @@
.data(nodes)
.enter().append("g")
.attr("class", "node")
- .attr("transform", function(d) { return "rotate(" + (d.x - 90) + ")translate(" + d.y + ")"; })
+ .attr("transform", function (d) {
+ return "rotate(" + (d.x - 90) + ")translate(" + d.y + ")";
+ })
node.append("circle")
.attr("r", 4.5);
node.append("text")
.attr("dy", ".31em")
- .attr("text-anchor", function(d) { return d.x < 180 ? "start" : "end"; })
- .attr("transform", function(d) { return d.x < 180 ? "translate(8)" : "rotate(180)translate(-8)"; })
- .text(function(d) { return d.name; });
+ .attr("text-anchor", function (d) {
+ return d.x < 180 ? "start" : "end";
+ })
+ .attr("transform", function (d) {
+ return d.x < 180 ? "translate(8)" : "rotate(180)translate(-8)";
+ })
+ .text(function (d) {
+ return d.name;
+ });
});
d3.select(self.frameElement).style("height", diameter - 150 + "px");
\ No newline at end of file