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import joblib | |
#fitting the clf variable to the training data | |
clf.fit(y_train, X_train) | |
#saving weights into a .sav file | |
weight = 'new_model.sav' | |
joblib.dump(clf, weight) |
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from joblib import load | |
#add the path of the file you wish to load | |
filename= './new_model.sav' | |
#your models weights are now stored in the variable loaded model | |
loaded_model = load("new_model.sav") |
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import joblib | |
clf.fit(y_train, X_train) | |
weight = 'new_model.sav' | |
joblib.dump(clf, weight) | |
#define a function and pass your parameters | |
def predict(A,B,C): | |
arr=[A,B,C] | |
y_test=[arr] | |
y_test=np.asarray(y_test) |
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import joblib | |
import multiprocessing as mp | |
clf.fit(y_train, X_train) | |
weight = 'new_model.sav' | |
joblib.dump(clf, weight) | |
#define a function and pass your parameters | |
def predict(A): |
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import joblib | |
import multiprocessing as mp | |
from joblib import load | |
#add the path of the file you wish to load | |
filename= './new_model.sav' | |
#your models weights are now stored in the variable loaded model | |
loaded_model = load("new_model.sav") | |
#define a function and pass your parameters |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import joblib | |
import multiprocessing as mp | |
from joblib import load | |
#add the path of the file you wish to load | |
filename= './new_model.sav' | |
#your models weights are now stored in the variable loaded model | |
loaded_model = load("new_model.sav") | |
#define a function and pass your parameters |