How to compute similarity(percentage) between two matrix/arrays. or find the closest array/matrix to a given array, on the basis of how similar their data value
I have defined few parameters in my config.yaml like as below. params: epochs: 10 batch_size: 128 num_classes: 10 loss_function: sparse_categorical_cros
I want to calculate shap values from a sklearn pipeline with a preprocessor and a model. When i do it with the code below I get 0 for all shape_values def creat
In scikit-learn, the GaussianMixture object has the method bic(X) that implements the Bayesian Information Criterion to choose the number of components that bet
I'm getting a keyerror 'initialized_diffuse' while calling the following API, probably after joblib.load(). import joblib .......... @routes.route("/forecast",
I built a random forest by RandomForestClassifier and plot the decision trees. What does the parameter "value" (pointed by red arrows) mean? And why the sum of
I want to customise the GRU-RNN cell from tensorflow. But i dont know which function i need to change from standart GRU from tensorflow. i want to modify GRU ce
I want to build a new computer for Data Science purposes. What do you think about this hardware: https://www.ldlc.com/configurateur-pc/23fe088422141bb69274a13ca
Is the GlobalAveragePooling1D Layer the same like calculating the mean with a custom Lambda Layer? The data is temporal, so x has shape (batch, time, features)
Does PyTorch's nn.Embedding support manually setting the embedding weights for only specific values? I know I could set the weights of the entire embedding laye
I'm trying to make a single variable regression using decision tree regression. However when I'm plotting the results. Multiple lines show in the plot just like
I have Keras model: pre-trained CV model + a few added layers on top I would want to be able to do model.predict before model.fit Q: how do I instantiate model
While training the model, I encountered the following problem: RuntimeError: CUDA out of memory. Tried to allocate 304.00 MiB (GPU 0; 8.00 GiB total capacity; 1
How can you measure how secure or private the new variables are relative to the real (actual) variables. I want to compare homomorphic encryption and differenti
I'm currently tackling a classification problem that needs prediction of the order of objects in a sequence, but not the object class itself. I've spent quite s
I have bunch of text data describing people's eduation. I have already done some basic NLP processing to those text data. An example would be this : XXX receive
I used Detectron2 to train a custom model with Instance Segmentation and worked well. There are several Tutorials on google colab with Detectron2 using Instance
I am trying to predict a single output value,y, using two input features. I read that regression models usually don't use any activation function, and even when
I am using Java API of vowpal wabbit to get predictions. I need raw prediction (same as -r output.txt) but I couldn't find any such method in VWMulticlassLearne
I have a project to hand in which requires me to develop a program in python which would recognise handwritten numbers given in the form of image(i imagine the