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Hi. I'm working on a SVM project in Python and I'm trying to use an SVM in Aduino. I'm trying to follow this example, but I don't know how to create a model with training data.
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I have originally discovered this effect using C version of libsvm, wrapped into C++ code, using real data.
Then I created a minimal snippet to reproduce it using libsvm in sklearn with random dat…
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Hi,
I have adapted the code of multiclass SVM to my dataset, it is working well, however I don't know how to use k-fold cross validation in the training loop. Any help or guidance would be very appr…
ilame updated
6 years ago
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`textmodel_svm()` does not work when the number of documents used to train the classifier exceeds 66,000 on a MacBook Pro with 32GB RAM.
```r
library(quanteda)
#> Package version: 2.0.1
#> Paral…
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hello
I want to train svm with my own dataset
I wonder about what is Positive_training_set & Negative_training_set
And, in this path, "DATASET\\POSITIVE\\" & "DATASET\\NEGATIVE\\", How should I put…
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Sklearn defines a `precomputed` option SVM's `kernel` parameter. In this case, instead of passing the training vectors, we pass the Gram matrix that contains kernel values between all training examp…
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Issues 1:
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In [5]: clf.fit(x,y)
2018-03-13 22:49:53,831 INFO [default] #instances…
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Hi ,
I have seen the wiki [Training on own dataset](https://github.com/davidsandberg/facenet/wiki/Train-a-classifier-on-own-images) using the frozen model 20170512-110547 provided in the Read me. …
knvpk updated
7 years ago
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on running after Q is being loaded this error comes:
self.model.train(samples, responses,params=svm_params) # inbuilt training function
TypeError: only size-1 arrays can be converted to Python sc…
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For the current version of the workflow, the classification is based on the average of the similarity scores. There are potentially better ways.
Talked together with Sonja about the classification…