单变量特征选择可视化

def solve():
    import pandas as pd
    import matplotlib.pyplot as plt
    from sklearn.feature_selection import SelectKBest, f_classif
    from sklearn.model_selection import train_test_split
    df = pd.read_csv(____)
    X = df.drop(____); y = df["____"]
    X_train, X_test, y_train, y_test = train_test_split(____)
    sk = SelectKBest(____).fit(____)
    scores = pd.Series(____).sort_values()
    selected = set(X.columns[sk.get_support()])
    colors = ["____" if c in selected else "____" for c in scores.index]
    plt.barh(range(len(____)), scores.values, color=colors)
    plt.yticks(range(len(____)), scores.index, fontsize=____); plt.title(____)
    plt.show()
    print("____".join(sorted(____)))