Question

我已经训练了一个模型，并使用python flask作为Web应用程序部署到了localhost。

在Web应用程序上看到的预测以“ LIL”（列表列表）矩阵形式显示

(0,1)   1
(0,3)   1

训练模型时没有得到这个问题，因为我使用了多标签二进制化器的逆变换

clf.predict(X_train,y_train)
pred = clf.predict(X_test)

pred_inverse = lb.inverse_transform(pred)
print(pred_inverse)

当我实现inverse_transform时，我得到的错误为

sklearn.exceptions.NotFittedError: This MultiLabelBinarizer instance is not fitted yet. Call 'fit' with appropriate arguments before using this method.

当我尝试使用时：

from sklearn.preprocessing import MultiabelBinarizer
lb = MultiLabelBinarizer()
pred_a = lb.fit_transform(prediction)

我收到错误消息

TypeError: unhashable type: 'lil_matrix'

我的完整代码（server.py）如下

 import numpy as np
from flask import Flask, request, jsonify, render_template
from sklearn.externals import joblib

app = Flask(__name__)
model = joblib.load(open('ensemble.sav', 'rb'))

@app.route('/')
def home():
    return render_template('index.html')

@app.route('/predict',methods=['POST'])
def predict():
    '''
    For rendering results on HTML GUI
    '''
    int_features = [int(x) for x in request.form.values()]
    final_features = [np.array(int_features)]
    prediction = model.predict(final_features)

    output = jsonify(prediction[0])

    return render_template('index.html', prediction_text='Mood of the song could be {}'.format(output))

@app.route('/predict_api',methods=['POST'])
def predict_api():
    '''
    For direct API calls trought request
    '''
    data = request.get_json(force=True)
    prediction = model.predict([np.array(list(data.values()))])

    output = prediction[0]
    return jsonify({'prediction': str(output)})

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

有人知道我如何在server.py本身中逆转换我的预测吗？

如何解码“ lil”矩阵预测

0 个答案: