Python, Technology, Stock Market, Data Science, Machine Learning.
self.fetch_stock_data() stock_data = self.preprocess_data(data) # Perform elbow curve to determine the optimal number of clusters inertia = [] for k in range(2, 15): kmeans = KMeans(n_clusters=k, n_init=10) kmeans.fit(stock_data) inertia.append(kmeans.inertia_) # Plot the elbow curve