特征选择：方差阈值

def solve():
    from sklearn.datasets import load_wine
    from sklearn.feature_selection import VarianceThreshold
    import numpy as np
    wine = load_wine()
    print(f"原始特征数: {wine.data.shape[1]}")
    variances = np.var(wine.data, axis=0)
    print("各特征方差:")
    for name, var in zip(wine.feature_names, variances):
        print(f"  {name}: {var:.4f}")
    threshold = 0.5
    selector = VarianceThreshold(threshold=threshold)
    X_selected = selector.fit_transform(wine.data)
    print(f"方差阈值: {threshold}")
    print(f"选择后特征数: {X_selected.shape[1]}")