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How do I create a feature vector for the training of an SVM?
The Next CEO of Stack Overflow2019 Community Moderator ElectionAspect based sentiment analysis using machine learning approachPre-processing (center, scale, impute) among training sets (different forms) and the test set - what is a good approach?Huge discrepancies in Logistic Regression and SVM using HOG features to identify an ObjectHow to include class as a featureHow can I run SVM on 500k rows with 81 columns?Supervised learning for image segmentationHow to use k-means outputs (extracted features) as SVM inputs?BOVW - Combine vocabulariesHow to quantify the performance of the classifier (multi-class SVM) using the test data?
$begingroup$
I have an understanding problem with implementing an SVM as a classifier for images.
The whole thing should be done in python.
Now, when I have extracted all the features, e.g. HOG, contours, textures, colors etc. How can I train with these characteristics an SVM.
By that I mean, how can I get these features into a shape so that I can directly train an SVM? Or in other words, how do I create a feature vector with these features?
Or can someone recommend me an example code?
Many thanks in advance
python feature-selection svm feature-extraction feature-scaling
asked Feb 26 at 17:18
Code NowCode Now
1
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bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I have an understanding problem with implementing an SVM as a classifier for images.
The whole thing should be done in python.
Now, when I have extracted all the features, e.g. HOG, contours, textures, colors etc. How can I train with these characteristics an SVM.
By that I mean, how can I get these features into a shape so that I can directly train an SVM? Or in other words, how do I create a feature vector with these features?
Or can someone recommend me an example code?
Many thanks in advance
python feature-selection svm feature-extraction feature-scaling
asked Feb 26 at 17:18
Code NowCode Now
1
$endgroup$
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I have an understanding problem with implementing an SVM as a classifier for images.
The whole thing should be done in python.
Now, when I have extracted all the features, e.g. HOG, contours, textures, colors etc. How can I train with these characteristics an SVM.
By that I mean, how can I get these features into a shape so that I can directly train an SVM? Or in other words, how do I create a feature vector with these features?
Or can someone recommend me an example code?
Many thanks in advance
python feature-selection svm feature-extraction feature-scaling
asked Feb 26 at 17:18
Code NowCode Now
1
$endgroup$
I have an understanding problem with implementing an SVM as a classifier for images.
The whole thing should be done in python.
Now, when I have extracted all the features, e.g. HOG, contours, textures, colors etc. How can I train with these characteristics an SVM.
By that I mean, how can I get these features into a shape so that I can directly train an SVM? Or in other words, how do I create a feature vector with these features?
Or can someone recommend me an example code?
Many thanks in advance
python feature-selection svm feature-extraction feature-scaling
python feature-selection svm feature-extraction feature-scaling
asked Feb 26 at 17:18
Code NowCode Now
1
asked Feb 26 at 17:18
Code NowCode Now
1
asked Feb 26 at 17:18
Code NowCode Now
1
asked Feb 26 at 17:18
Code NowCode Now
1
asked Feb 26 at 17:18
Code NowCode Now
1
1
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 10 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
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$begingroup$
SVM in scikit learn, (like all other algorithms in scikit-learn) currently only support taking NumPy arrays as the input to the algorithm.
As long as you are using a Numpy array you should have no problem just passing your data through by calling:
smv = smv.SVC()
svm.fit(X, y)
On your data.
answered Feb 27 at 2:52
EthanEthan
588224
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$begingroup$
SVM in scikit learn, (like all other algorithms in scikit-learn) currently only support taking NumPy arrays as the input to the algorithm.
As long as you are using a Numpy array you should have no problem just passing your data through by calling:
smv = smv.SVC()
svm.fit(X, y)
On your data.
answered Feb 27 at 2:52
EthanEthan
588224
$endgroup$
add a comment |
$begingroup$
SVM in scikit learn, (like all other algorithms in scikit-learn) currently only support taking NumPy arrays as the input to the algorithm.
As long as you are using a Numpy array you should have no problem just passing your data through by calling:
smv = smv.SVC()
svm.fit(X, y)
On your data.
answered Feb 27 at 2:52
EthanEthan
588224
$endgroup$
add a comment |
$begingroup$
SVM in scikit learn, (like all other algorithms in scikit-learn) currently only support taking NumPy arrays as the input to the algorithm.
As long as you are using a Numpy array you should have no problem just passing your data through by calling:
smv = smv.SVC()
svm.fit(X, y)
On your data.
answered Feb 27 at 2:52
EthanEthan
588224
$endgroup$
SVM in scikit learn, (like all other algorithms in scikit-learn) currently only support taking NumPy arrays as the input to the algorithm.
As long as you are using a Numpy array you should have no problem just passing your data through by calling:
smv = smv.SVC()
svm.fit(X, y)
On your data.
answered Feb 27 at 2:52
EthanEthan
588224
answered Feb 27 at 2:52
EthanEthan
588224
answered Feb 27 at 2:52
EthanEthan
588224
answered Feb 27 at 2:52
EthanEthan
588224
588224
add a comment |
add a comment |
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