cs224u sst_02_hand_built_features Wrapper for LogisticRegression

cs224u sst_02_hand_built_features Wrapper for LogisticRegression

上一篇博客(https://duanzhihua.blog.csdn.net/article/details/105981617)我们讲解了BasicSGDClassifier ，它在SST上做得很好！但我们可能不想依赖BasicSGDClassifier ，相反，我们希望依靠sklearn。下面是一个简单的sklearn.linear.model.LogisticRegression封装器，使用了build-dataset加载数据。 

def fit_softmax_classifier(X, y):    
    """Wrapper for `sklearn.linear.model.LogisticRegression`. This is 
    also called a Maximum Entropy (MaxEnt) Classifier, which is more 
    fitting for the multiclass case.
    
    Parameters
    ----------
    X : 2d np.array
        The matrix of features, one example per row.
    y : list
        The list of labels for rows in `X`.
    
    Returns
    -------
    sklearn.linear.model.LogisticRegression
        A trained `LogisticRegression` instance.
    
    """
    mod = LogisticRegression(
        fit_intercept=True, 
        solver='libline

来源：oschina

链接：https://my.oschina.net/u/4324735/blog/4275274