Category "classification"

Neural Network for Regression with tflearn

My question is about coding a neural network which does regression (and NOT classification) using tflearn. Dataset: fixed acidity volatile acidity citric acid

tensorflow automatic accuracy calculation for multilabel classifier

I am fitting a multilabel classifier to (train_x, train_y) while monitoring the loss and accuracy on a validation set (val_x, val_y): classification_model.compi

SKLearn: Getting distance of each point from decision boundary?

I am using SKLearn to run SVC on my data. from sklearn import svm svc = svm.SVC(kernel='linear', C=C).fit(X, y) I want to know how I can get the distance of

Scalable/Iterative Large Data Frame Dimensionality Reduction R

I often have truly large data frames (ie 10 to 40 columns, millions to hundreds of millions of rows) that I would like to perform dimensionality reduction on in

Classification metrics can't handle a mix of binary and continuous targets [duplicate]

I try to train and test several scikit-learn models and attempt to print off the accuracy. Only some of these models work, others fail with th

ValueError: Input 0 of layer is incompatible with the layer: expected shape=(None, 224, 224, 3), found shape=(224, 224, 3)

"after converting the dataset to the tfrecord file format, I tried to train the model I created with it, but I couldn't convert it to the input format suitable

Difference between absdiff and normal subtraction in OpenCV

I am currently planning on training a binary image classification model. The images I want to train on are the difference between two original pictures. In ot

Only two distinct values of probabilities in Logistic regression output

I am running a logistic regression in R and extracting the predicted probabilities for a test data of about 15,000 rows using predict(modelglm, test_data, type

Which algorithm is the best based on P-Values

I used the following code: plt.figure(figsize = (7, 7)) plt.boxplot([totalP['poly'], totalP['rbf'], totalP['linear'], totalP['gf']]) plt.xticks(np.arange(1, 5),

Scikit-Learn: How to retrieve prediction probabilities for a KFold CV?

I have a dataset that consists of images and associated descriptions. I've split these into two separate datasets with their own classifiers (visual and textual

Weight tensor should be defined either for all 1000 classes or no classes but got weight tensor of shape: [5]

I'm trying to use VGG16 for ** 5 classes data set**. I've already added 5 new layers to adjust the output for logit as 5. model = models.vgg16(pretrained=True)

Metrics F1 warning zero division

I want to calculate the F1 score of my models. But I receive a warning and get a 0.0 F1-score and I don't know what to do. here is the source code: def model_

Sparse Categorical CrossEntropy shape problem with Keras

I have a multiclass problem where an image can be one of three classes (Masked, UnMasked, Hybrid). I am using image_dataset_from_directory from keras preprocess

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