Pandas :TypeError: float() argument must be a string or a number, not 'pandas._libs.interval.Interval'

Pandas :TypeError: float() argument must be a string or a number, not 'pandas._libs.interval.Interval'

我正在尝试做心脏病的机器学习练习题,来自 kaggle 的数据集。 然后我尝试将数据分成训练集和测试集,然后将模型组合成单个函数并进行预测,这个错误出现在 jupyter notebook 中。

这是我的代码:

# Split data into X and y
X = df.drop("target", axis=1)
y = df["target"]

拆分

# Split data into train and test sets
np.random.seed(42)

# Split into train & test set
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2)

预测函数

    # Put models in a dictionary
models = {"Logistic Regression": LogisticRegression(),
          "KNN": KNeighborsClassifier(),
          "Random Forest": RandomForestClassifier()}

# Create a function to fit and score models
def fit_and_score(models, X_train, X_test, y_train, y_test):
    """
    Fits and evaluates given machine learning models.
    models : a dict of differetn Scikit-Learn machine learning models
    X_train : training data (no labels)
    X_test : testing data (no labels)
    y_train : training labels
    y_test : test labels
    """
    # Set random seed
    np.random.seed(42)
    # Make a dictionary to keep model scores
    model_scores = {}
    # Loop through models
    for name, model in models.items():
        # Fit the model to the data
        model.fit(X_train, y_train)
        # Evaluate the model and append its score to model_scores
        model_scores[name] = model.score(X_test, y_test)
    return model_scores

当我 运行 这段代码时,出现了那个错误

    model_scores = fit_and_score(models=models,
                             X_train=X_train,
                             X_test=X_test,
                             y_train=y_train,
                             y_test=y_test)

model_scores

这是错误

您的 X_trainy_train 或两者似乎包含非浮点数的条目。

在代码中的某个位置,尝试使用

X_train = X_train.astype(float)
y_train = y_train.astype(float)
X_test = X_test.astype(float)
y_test = y_test.astype(float)

这将起作用并且错误将消失,或者其中一个转换将失败,此时您将需要决定如何(或是否)将数据编码为浮点数。