Ревізії hambuger_case.java

Ade9 ревизій цього gist 1 month ago. До ревизії

1 file changed, 2 insertions, 2 deletions

hambuger_case.java

			@@ -259,9 +259,9 @@ public class KMeans {
259	259		_ _ __________ ____ _
260	260		for (int i = 0; i < dataPoints.size(); i++) {
261	261		_ _ __________ ____ _
262		-	______ ___ _______ ____ _____ _ _______ __ _______ ________ ___ _
	262	+	______ ___ _______ _ ________ ___ _
263	263		System.out.println("Data point " + (i + 1) + " belongs to cluster " + (clusters.get(i) + 1));
264		-	______ ___ _______ ____ _____ _ _______ __ _______ ________ ___ _
	264	+	______ ___ _______ _ ________ ___ _
265	265		}
266	266		}
267	267		}

Ade9 ревизій цього gist 1 month ago. До ревизії

1 file changed, 267 insertions

hambuger_case.java(файл створено)

		@@ -0,0 +1,267 @@
1	+	____ ____ _________
2	+	import java.util.ArrayList;
3	+	____ ____ _________
4	+	____ ____ ____
5	+	import java.util.List;
6	+	____ ____ ____
7	+	____ ____ ______
8	+	import java.util.Random;
9	+	____ ____ ______
10	+	______
11	+	public class KMeans {
12	+	______
13	+	_
14	+	private static int k;
15	+	_
16	+	_____________
17	+	private static int maxIterations;
18	+	_____________
19	+	____ ______ _________
20	+	private static List<Double[]> centroids;
21	+	____ ______ _________
22	+	____ _______ ______ ____ ______ __________ _ _____________
23	+	public static List<Integer> kMeans(List<Double[]> dataPoints, int k, int maxIterations) {
24	+	____ _______ ______ ____ ______ __________ _ _____________
25	+	______ _ _
26	+	KMeans.k = k;
27	+	______ _ _
28	+	______ _____________ _____________
29	+	KMeans.maxIterations = maxIterations;
30	+	______ _____________ _____________
31	+	_________ _________
32	+	centroids = new ArrayList<>();
33	+	_________ _________
34	+	_________ ___________________ __________
35	+	centroids = initializeCentroids(dataPoints);
36	+	_________ ___________________ __________
37	+	____ _______ __________________ _________
38	+	List<Integer> clusterAssignments = new ArrayList<>();
39	+	____ _______ __________________ _________
40	+	_ _ _ _____________ _
41	+	for (int i = 0; i < maxIterations; i++) {
42	+	_ _ _ _____________ _
43	+	__________________ ______________ __________
44	+	clusterAssignments = assignClusters(dataPoints);
45	+	__________________ ______________ __________
46	+	____ ______ ____________ _______________ __________ __________________
47	+	List<Double[]> newCentroids = updateCentroids(dataPoints, clusterAssignments);
48	+	____ ______ ____________ _______________ __________ __________________
49	+	_________ ____________
50	+	if (converged(newCentroids)) {
51	+	_________ ____________
52	+	break;
53	+	}
54	+	_________ ____________
55	+	centroids = newCentroids;
56	+	_________ ____________
57	+	}
58	+	__________________
59	+	return clusterAssignments;
60	+	__________________
61	+	}
62	+	____ ______ ___________________ ____ __________
63	+	private static List<Double[]> initializeCentroids(List<Double[]> dataPoints) {
64	+	____ ______ ___________________ ____ __________
65	+	____ ______ _________ _________
66	+	List<Double[]> centroids = new ArrayList<>();
67	+	____ ______ _________ _________
68	+	______ ______ ______
69	+	Random random = new Random();
70	+	______ ______ ______
71	+	_ _ _ _
72	+	for (int i = 0; i < k; i++) {
73	+	_ _ _ _
74	+	_____ ______ _______ __________ ____
75	+	int index = random.nextInt(dataPoints.size());
76	+	_____ ______ _______ __________ ____
77	+	_________ ___ __________ ___ _____ _____
78	+	centroids.add(dataPoints.get(index).clone());
79	+	_________ ___ __________ ___ _____ _____
80	+	}
81	+	_________
82	+	return centroids;
83	+	_________
84	+	}
85	+	____ _______ ______________ ____ ______ __________
86	+	private static List<Integer> assignClusters(List<Double[]> dataPoints) {
87	+	____ _______ ______________ ____ ______ __________
88	+	____ _______ __________________ _________
89	+	List<Integer> clusterAssignments = new ArrayList<>();
90	+	____ _______ __________________ _________
91	+	______ _____ __________
92	+	for (Double[] point : dataPoints) {
93	+	______ _____ __________
94	+	______ ___________ ______ _________
95	+	Double minDistance = Double.MAX_VALUE;
96	+	______ ___________ ______ _________
97	+	_______ _
98	+	int cluster = 0;
99	+	_______ _
100	+	_ _ _________ ____ _
101	+	for (int i = 0; i < centroids.size(); i++) {
102	+	_ _ _________ ____ _
103	+	______ ________ _________________ _____ _________ ___ _
104	+	Double distance = calculateDistance(point, centroids.get(i));
105	+	______ ________ _________________ _____ _________ ___ _
106	+	________ ___________
107	+	if (distance < minDistance) {
108	+	________ ___________
109	+	___________ ________
110	+	minDistance = distance;
111	+	___________ ________
112	+	_______ _
113	+	cluster = i;
114	+	_______ _
115	+	}
116	+	}
117	+	__________________ ___ _______
118	+	clusterAssignments.add(cluster);
119	+	__________________ ___ _______
120	+	}
121	+	__________________
122	+	return clusterAssignments;
123	+	__________________
124	+	}
125	+	______ _________________ ______ ______
126	+	private static Double calculateDistance(Double[] point1, Double[] point2) {
127	+	______ _________________ ______ ______
128	+	______ ________ _ _
129	+	Double distance = 0.0;
130	+	______ ________ _ _
131	+	_ _ ______ ______ _
132	+	for (int i = 0; i < point1.length; i++) {
133	+	_ _ ______ ______ _
134	+	________ ____ ___ ______ _ ______ _
135	+	distance += Math.pow(point1[i] - point2[i], 2);
136	+	________ ____ ___ ______ _ ______ _
137	+	}
138	+	____ ____ ________
139	+	return Math.sqrt(distance);
140	+	____ ____ ________
141	+	}
142	+	____ ______ _______________ ____ ______ __________ ____ _______ __________________
143	+	private static List<Double[]> updateCentroids(List<Double[]> dataPoints, List<Integer> clusterAssignments) {
144	+	____ ______ _______________ ____ ______ __________ ____ _______ __________________
145	+	____ ______ ____________ _________
146	+	List<Double[]> newCentroids = new ArrayList<>();
147	+	____ ______ ____________ _________
148	+	__________ __________ ___ ______
149	+	int dimensions = dataPoints.get(0).length;
150	+	__________ __________ ___ ______
151	+	_ _ _ _
152	+	for (int i = 0; i < k; i++) {
153	+	_ _ _ _
154	+	____ ______ _______________ _________
155	+	List<Double[]> pointsInCluster = new ArrayList<>();
156	+	____ ______ _______________ _________
157	+	_ _ __________ ____ _
158	+	for (int j = 0; j < dataPoints.size(); j++) {
159	+	_ _ __________ ____ _
160	+	__________________ ___ _ _
161	+	if (clusterAssignments.get(j) == i) {
162	+	__________________ ___ _ _
163	+	_______________ ___ __________ ___ _
164	+	pointsInCluster.add(dataPoints.get(j));
165	+	_______________ ___ __________ ___ _
166	+	}
167	+	}
168	+	_______________ _______
169	+	if (pointsInCluster.isEmpty()) {
170	+	_______________ _______
171	+	____________ ___ ______ __________
172	+	newCentroids.add(new Double[dimensions]);
173	+	____________ ___ ______ __________
174	+	continue;
175	+	}
176	+	______ ___________ ______ __________
177	+	Double[] newCentroid = new Double[dimensions];
178	+	______ ___________ ______ __________
179	+	_ _ __________ _
180	+	for (int d = 0; d < dimensions; d++) {
181	+	_ _ __________ _
182	+	___
183	+	double sum = 0.0;
184	+	___
185	+	______ _____ _______________
186	+	for (Double[] point : pointsInCluster) {
187	+	______ _____ _______________
188	+	___ _____ _
189	+	sum += point[d];
190	+	___ _____ _
191	+	}
192	+	___________ _ ___ _______________ ____
193	+	newCentroid[d] = sum / pointsInCluster.size();
194	+	___________ _ ___ _______________ ____
195	+	}
196	+	____________ ___ ___________
197	+	newCentroids.add(newCentroid);
198	+	____________ ___ ___________
199	+	}
200	+	____________
201	+	return newCentroids;
202	+	____________
203	+
204	+	}
205	+	_________ ____ ____________
206	+	private static boolean converged(List<Double[]> newCentroids) {
207	+	_________ ____ ____________
208	+	_ _ _________ ____ _
209	+	for (int i = 0; i < centroids.size(); i++) {
210	+	_ _ _________ ____ _
211	+	_________ ___ _ ______ ____________ ___ _
212	+	if (!centroids.get(i).equals(newCentroids.get(i))) {
213	+	_________ ___ _ ______ ____________ ___ _
214	+
215	+	return false;
216	+	}
217	+	}
218	+	return true;
219	+	}
220	+	____ ______ ____
221	+	public static void main(String[] args) {
222	+	____ ______ ____
223	+	____ ______ __________ _________
224	+	List<Double[]> dataPoints = new ArrayList<>();
225	+	____ ______ __________ _________
226	+	__________ ___ ______
227	+	dataPoints.add(new Double[]{1.0, 2.0});
228	+	__________ ___ ______
229	+	__________ ___ ______
230	+	dataPoints.add(new Double[]{1.5, 1.8});
231	+	__________ ___ ______
232	+	__________ ___ ______
233	+	dataPoints.add(new Double[]{5.0, 8.0});
234	+	__________ ___ ______
235	+	__________ ___ ______
236	+	dataPoints.add(new Double[]{8.0, 8.0});
237	+	__________ ___ ______
238	+	__________ ___ ______
239	+	dataPoints.add(new Double[]{1.0, 0.6});
240	+	__________ ___ ______
241	+	__________ ___ ______
242	+	dataPoints.add(new Double[]{9.0, 11.0});
243	+	__________ ___ ______
244	+	_
245	+	int k = 2;
246	+	_
247	+	_____________
248	+	int maxIterations = 100;
249	+	_____________
250	+
251	+
252	+
253	+	____ _______ ________ ______ __________ _ _____________
254	+	List<Integer> clusters = kMeans(dataPoints, k, maxIterations);
255	+	____ _______ ________ ______ __________ _ _____________
256	+
257	+
258	+
259	+	_ _ __________ ____ _
260	+	for (int i = 0; i < dataPoints.size(); i++) {
261	+	_ _ __________ ____ _
262	+	______ ___ _______ ____ _____ _ _______ __ _______ ________ ___ _
263	+	System.out.println("Data point " + (i + 1) + " belongs to cluster " + (clusters.get(i) + 1));
264	+	______ ___ _______ ____ _____ _ _______ __ _______ ________ ___ _
265	+	}
266	+	}
267	+	}

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