如何部署机器学习模型以使用多个特征数据进行预测

Question

I have a trained machine learning model need to be deploy. It is trained with mutltiple features but how to use that model to predict with multiple feature data. for example i need to use these feature data to predict the result

input = [46.8,11,7,0.686563,6.540829e-08,1.133174e-09]

i used following code but itseems predict() is working only for single feature data.

from sklearn.externals import joblib
model = joblib.load('SVM_LINEAR')
model.predict([46.8,11,7,0.686563,6.540829e-08,1.133174e-09])

Answer 1

I think you need to make a numpy array of features and then pass it inside model.predict ie

import numpy as np
from sklearn.externals import joblib
model = joblib.load('SVM_LINEAR')
model.predict(np.asarray([46.8,11,7,0.686563,6.540829e-08,1.133174e-09]))

or you can try this:

import numpy as np
from sklearn.externals import joblib
model = joblib.load('SVM_LINEAR')
model.predict([[46.8,11,7,0.686563,6.540829e-08,1.133174e-09]])