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Questions - svm

NameError: name 'GridSearchCV' is not defined. I have done the import though : from sklearn.model_selection import GridSearchCV

NameError Traceback (most recent call last) C:\Users\VAISHN~1\AppData\Local\Temp/ipykernel_6520/2922578464.py in 3 'kernel': ['rbf']} 4 ----> 5 optimal_params...
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Vaishnavi

python

machine-learning

svm

nameerror

gridsearchcv

Votes: 0

Answers: 1

Latest Answer

There could be 3 reasons on why this is happening: You haven't installed the library in your environment. You can solve this using the code below: python -m pip install --upgrade pip pip install -U ...
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Allan Chua

Training OpenCV model on multiple pictures based on color, not on shape AKA "Banana ripeness detector"

So long story short, I'm looking for an OpenCV model that does training on multiple image sets based on color, not on shape. Like a FaceRegonition algorithm (Fisherfacerecognizer, EigenFaces, Lbphface...
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TheCulprit

c++

opencv

svm

face-recognition

color-detection

Votes: 0

Answers: 0

predict job title on the basis of skills

I'm working on a project where I need to predict if a person should be frontend dev, backend dev, DevOps eng or data scientist, etc on the basis of his skills. For example: Sam has skills ['python','s...
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rawheel

tensorflow

nlp

artificial-intelligence

data-science

svm

Votes: 0

Answers: 2

Latest Answer

Here I am assuming that the methodology that you want to adopt is a ML model and not a string matching problem. The way that I would approach this problem would be to do is: Create a one-hot encoding...
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Prajual Pillai

Support vector machine with multioutput ValueError: The number of classes has to be greater than one; got 1 class

I am stuck on an error when trying to run a multioutput classifier that is using a support vector machine. The test set y_train_svm looks like this: array([[1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1...
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Tobman

python

machine-learning

svm

Votes: 0

Answers: 1

Latest Answer

Try to cast the values of your train/test-arrays as integer like y_train_svm.astype(np.int8), then run your training-code where you use fit() again.
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Artur

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