Question

我正在尝试预测一个人是否患有某种疾病。通过在HTML页面上传递输入并能够预测值，但无法在HTML页面上显示精度。Error=“ TypeError：预期的序列或类似数组的内容，得到了“。下面是我的代码。请提供一些帮助问题发生了

    from flask import Flask, redirect, url_for, request, render_template
    import numpy as np
    import pandas as pd
    from sklearn.ensemble import GradientBoostingClassifier,RandomForestClassifier
    from sklearn.model_selection import train_test_split
    from sklearn.metrics import accuracy_score,precision_score,recall_score,auc,roc_curve

    app = Flask(__name__)

    Data = pd.read_csv('data\\new_heart.csv')
    y = Data['target']
    Data.drop("target", axis=1, inplace=True)
    X = Data

    x_train, x_test, y_train, y_test = train_test_split(X, y, random_state=42)

    Model = GradientBoostingClassifier(verbose=1, learning_rate=0.5,warm_start=True)
    Model.fit(x_train, y_train)

    y_pred=0
    def generate_prediction(input):


        y_pred = Model.predict(input)
        return  y_pred

    @app.route('/')
    def home():

        return render_template('disease.html')


    @app.route('/get_value', methods=['GET', 'POST'])
    def get_price():
        input = request.form
        input = np.array(list(input.values())).reshape(1,-1)
        print(input)

        price = generate_prediction(input)
        if price == 0:
            return "Not Suffering from a disease {}".format(price,accuaracy())
        else:
            return "Suffering from a disease {}{}".format(price,accuaracy())





    def accuaracy():


        print("Accuracy(GradientBoostingClassifier)\t:" + str(accuracy_score(y_test, y_pred)))
        print("Precision(GradientBoostingClassifier)\t:" + str(precision_score(y_test, y_pred)))
        print("Recall(GradientBoostingClassifier)\t:" + str(recall_score(y_test, y_pred)))


    if __name__ == '__main__':
        app.run(debug=True)

disease.html

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Title</title>
</head>
<body>
    <form action=" http://127.0.0.1:5000/get_value" method="POST">

    <p>age <input type="text" name="t1"/></p>
    <p>sex <input type="text" name="t2"/></p>
    <p>cp <input type="text" name="t3"/></p>
    <p>trestbps <input type="text" name="t4"/></p>
        <p>chol <input type="text" name="t5"/></p>
        <p>fbs <input type="text" name="t6"/></p>
        <p>restecg <input type="text" name="t7"/></p>
        <p>thalach <input type="text" name="t8"/></p>
        <p>exang <input type="text" name="t9"/></p>
        <p>oldspeak <input type="text" name="t10"/></p>
    <p>slope <input type="text" name="t11"/></p>
        <p>ca <input type="text" name="t12"/></p>
        <p>thal <input type="text" name="t13"/></p>

    <p><input type="submit" value="submit"/></p>
    </form>
</body>

traceback (most recent call last):
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 2309, in __call__
    return self.wsgi_app(environ, start_response)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 2295, in wsgi_app
    response = self.handle_exception(e)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 1741, in handle_exception
    reraise(exc_type, exc_value, tb)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\_compat.py", line 35, in reraise
    raise value
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 2292, in wsgi_app
    response = self.full_dispatch_request()
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 1815, in full_dispatch_request
    rv = self.handle_user_exception(e)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 1718, in handle_user_exception
    reraise(exc_type, exc_value, tb)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\_compat.py", line 35, in reraise
    raise value
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 1813, in full_dispatch_request
    rv = self.dispatch_request()
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\flask\app.py", line 1799, in dispatch_request
    return self.view_functions[rule.endpoint](**req.view_args)
  File "C:\Users\Indu\PycharmProjects\WebApp\HeartDisease.py", line 43, in get_price
    return "Suffering from a disease {}{}".format(price,accuaracy())
  File "C:\Users\Indu\PycharmProjects\WebApp\HeartDisease.py", line 52, in accuaracy
    print("Accuracy(GradientBoostingClassifier)\t:" + str(accuracy_score(y_test, y_pred)))
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\sklearn\metrics\classification.py", line 176, in accuracy_score
    y_type, y_true, y_pred = _check_targets(y_true, y_pred)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\sklearn\metrics\classification.py", line 71, in _check_targets
    check_consistent_length(y_true, y_pred)
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\sklearn\utils\validation.py", line 231, in check_consistent_length
    lengths = [_num_samples(X) for X in arrays if X is not None]
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\sklearn\utils\validation.py", line 231, in <listcomp>
    lengths = [_num_samples(X) for X in arrays if X is not None]
  File "C:\Users\Indu\PycharmProjects\WebApp\venv\lib\site-packages\sklearn\utils\validation.py", line 138, in _num_samples
    type(x))
TypeError: Expected sequence or array-like, got <class 'int'>

Answer 1

在您的accuracy()函数中，您需要将数组传递给Sklearn指标。现在，您只传递一个int值。确保y_test和y_pred是数组，即使它们只是一个元素。

Answer 2

由于input的重塑为（-1,1），因此出现错误。由于y_pred = Model.predict(input)中的形状，您将始终获得整数值。因为您将输入一维清单作为输入

因此要获取list，您的输入应等于x_test，这样您就可以获取y_pred。

还请注意，在accuracy_score(y_test, y_pred)中，两个参数的长度应相同

错误：预期的序列或数组状，得到<class'int'=“”>“

2 个答案: