Kmeans update

Class_Mod/KMEANS_.py

+from Packages import *
+
+class Sk_Kmeans:
+    def __init__(self, x, max_clusters):
+        self.x = x
+        self.max_clusters = max_clusters
+
+        self.inertia = pd.DataFrame()
+        for i in range(1, max_clusters+1):
+            model = KMeans(n_clusters = i, init = 'k-means++', random_state = 42)
+            model.fit(x)
+            self.inertia[f'{i}_clust']= [model.inertia_]
+        self.inertia.index = ['inertia']
+
+    @property
+    def inertia_(self):
+        return self.inertia
+
+    def fit_optimal(self, nclusters):
+        model = KMeans(n_clusters = nclusters, init = 'k-means++', random_state = 42)
+        model.fit(self.x)
+        yp = model.predict(self.x)
+        num_colors = nclusters
+        colors = ['#' + ''.join([random.choice('0123456789ABCDEF') for _ in range(6)]) for _ in range(num_colors)]
+        col = np.array(['#' + ''.join([random.choice('0123456789ABCDEF') for _ in range(6)]) for _ in range(self.x.shape[0])])
+        for i in range(nclusters):
+            ss = np.where(yp==i)
+            col[ss] = colors[i]
+
+
+        return self.x, col
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