# PCAの実行と累積寄与率のカーブ pca = PCA() pca.fit(matrix2) # 寄与率と累積寄与率の計算 explained_variance_ratio = pca.explained_variance_ratio_ cumulative_explained_variance = np.cumsum(explained_variance_ratio) # 累積寄与率のカーブをプロット plt.figure(figsize=(8, 6)) plt.plot(range(1, len(cumulative_explained_variance) + 1), cumulative_explained_variance, marker='o') plt.xlabel("Number of Components") plt.ylabel("Cumulative Explained Variance") plt.title("Cumulative Explained Variance by Number of PCA Components") plt.grid(True) plt.show()