博雅数据机器学习08

博雅数据机器学习08

PCA降维

from sklearn.decomposition import PCA

import matplotlib.pyplot as plt

%matplotlib inline

 

# pca降维过程

pca = PCA(n_components=2)

X_pca = pca.fit_transform(X)

 

# 计算第一主成分方差占比

fpc = pca.explained_variance_ratio_[0]

 

# 在低维空间中绘图

colors = ['green','c','orange'] # 色系选择

f,ax = plt.subplots(figsize=(6,6))

for color, label in zip(colors, y.unique()):

    plt.scatter(X_pca[y == label, 0],

                X_pca[y == label, 1],

                color=color,

                lw=2,

                label=label)

plt.legend(loc="upper center")

plt.title("PCA of iris dataset")