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I fount that N_vector size of the exported C is not the same with the size of the training sample.
Method: I use the sample code on https://github.com/nok/sklearn-porter/blob/stable/examples/estimator/classifier/SVC/c/basics.pct.ipynb to export the C code. I split the training and test set of 90%:10% by the following code:
from sklearn.model_selection import train_test_split irisdata = load_iris() X=irisdata.data y=irisdata.target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=True) print(X_train.shape,y_train.shape) print(X_test.shape,y_test.shape)
Output: (135, 4) (135,)(15, 4) (15,)
(135, 4) (135,)(15, 4) (15,)
Then I train the model:
clf = svm.SVC(C=1.0, gamma = 0.001, kernel = 'rbf', random_state = 0) clf.fit(X_train,y_train)
Finally I exportthe code:
porter = Porter(clf, language = 'c') output = porter.export() print(output)
But I got:
#include <stdlib.h> #include <stdio.h> #include <math.h> #define N_FEATURES 4 #define N_CLASSES 3 #define N_VECTORS 132 #define N_ROWS 3 #define N_COEFFICIENTS 2 #define N_INTERCEPTS 3 #define KERNEL_TYPE 'r' #define KERNEL_GAMMA 0.001 #define KERNEL_COEF 0.0 #define KERNEL_DEGREE 3 double vectors[132][4] = {{4.4, 3.2, 1.3, 0.2}, {5.4, 3.4, 1.5, 0.4}, {5.0, 3.2, 1.2, 0.2}, {5.0, 3.5, 1.3, 0.3}, {5.5, 4.2, 1.4, 0.2}, {5.1, 3.8, 1.5, 0.3}, {5.3, 3.7, 1.5, 0.2}, {5.2, 3.4, 1.4, 0.2}, {5.1, 3.5, 1.4, 0.3}, {5.7, 3.8, 1.7, 0.3}, {5.0, 3.6, 1.4, 0.2}, {4.8, 3.0, 1.4, 0.3}, {5.1, 3.4, 1.5, 0.2}, {5.5, 3.5, 1.3, 0.2}, {4.8, 3.4, 1.6, 0.2}, {4.8, 3.0, 1.4, 0.1}, {4.7, 3.2, 1.3, 0.2}, {4.6, 3.4, 1.4, 0.3}, {5.1, 3.8, 1.6, 0.2}, {5.4, 3.7, 1.5, 0.2}, {4.9, 3.1, 1.5, 0.2}, {5.2, 4.1, 1.5, 0.1}, {4.4, 3.0, 1.3, 0.2}, {5.2, 3.5, 1.5, 0.2}, {5.1, 3.3, 1.7, 0.5}, {4.9, 3.1, 1.5, 0.1}, {5.7, 4.4, 1.5, 0.4}, {4.5, 2.3, 1.3, 0.3}, {5.0, 3.4, 1.6, 0.4}, {5.0, 3.5, 1.6, 0.6}, ... ......
The N_VECTORS is 132 instead of 135.
I tried other split ratios and the following are some examples:
The text was updated successfully, but these errors were encountered:
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I fount that N_vector size of the exported C is not the same with the size of the training sample.
Method:
I use the sample code on https://github.com/nok/sklearn-porter/blob/stable/examples/estimator/classifier/SVC/c/basics.pct.ipynb
to export the C code.
I split the training and test set of 90%:10% by the following code:
Output:
(135, 4) (135,)(15, 4) (15,)
Then I train the model:
Finally I exportthe code:
But I got:
The
N_VECTORS is 132 instead of 135.
I tried other split ratios and the following are some examples:
The text was updated successfully, but these errors were encountered: