Is there a way to use GridSearchCV or any other built-in sklearn function to find the best hyper-parameters for OneClassSVM classifier? What I currently do, is perform the search myself using trai...

This post is about the differences between LogisticRegressionCV, GridSearchCV and cross_val_score. Consider the following setup: import numpy as np from sklearn.datasets import load_digits from sk...

I am searching for a hyperparameter tune package for code written directly in Tensorflow (not Keras or Tflearn). Could you make some suggestion?

I'll fully admit that I may be setting up the conditional space wrong here but for some reason, I just can't get this to function at all. I am attempting to use hyperopt to tune a logistic regressi...

Is there any rule of thumb to initialize the num_leaves parameter in lightgbm. For example for 1000 featured dataset, we know that with tree-depth of 10, it can cover the entire dataset, so we can ...

I am trying to perform a hyper parameter optimization task for a LSTM (pure Tensorflow) with Tune. I followed their example on the hyperopt algorithm. In the example they have used the below line i...

I am working on using hyperopt to tune my ML model but having troubles in using the qloguniform as the search space. I am giving the example from official wiki and changed the search space. impor...

Is it possible to tune hyperparameters using ML Engine to train the model locally? The documentation only mentions training with hyperparameter tuning in the cloud (submitting a job), and has no me...

Is there any way to specify hyper-parameter optimisation like Hyperopt or other in the config file of object detection API to fine tune the model?

I am trying to find best hyperparameters for my trained doc2vec gensim model which takes a document as an input and create its document embeddings. My train data consists of text documents but it d...

I'm using Gridsearch function from hypopt package to do my hyperparameter searching using specified validation set. The default metric for classification seems to be accuracy (not very sure). Here ...

I have a FFNN with 2 hidden layers for a regression task that overfits almost immediately (epoch 2-5, depending on # hidden units). (ReLU, Adam, MSE, same # hidden units per layer, tf.keras) 32 ne...

I am using the LightFM recommender library on my dataset, which gives me the results in the image below. NUM_THREADS = 4 NUM_COMPONENTS = 30 NUM_EPOCHS = 5 ITEM_ALPHA = 1e-6 LEARNING_RATE = 0.00...

I've used Scikit-learn's GridSearchCV before to optimize the hyperparameters of my models, but just wondering if a similar tool exists to optimize hyperparameters for Tensorflow (for instance numbe...

Well I'm trying to understand how and at which point in an algorithm to apply the Kfold CV and GridSearchCV. Also if i understand correctly GridSearchCV is used for hyperparameter tuning i.e. what ...

I got a weird result from vw, which uses online learning scheme for logistic regression. And when I add --l1 or --l2 regularization then I got all predictions at 0.5 (that means all features are 0)...

I am trying to fit a logistic regression model in R using the caret package. I have done the following: model <- train(dec_var ~., data=vars, method="glm", family="binomial", trControl = ctrl,...

I'm using GridSearchCV, and after each iteration I want to save the clf.cv_results_ property to a file, (just in case that the process will crash in the middle). I tried looking for a solution bu...

I am trying to optimize the hyperparameters of my NN using Keras and sklearn. I am wrapping up with KerasClassifier (it´s a classification problem). I am trying to optimize the number of hidden lay...

In Convolutional Neural Network (CNN), a filter is select for weights sharing. For example, in the following pictures, a 3x3 window with the stride (distance between adjacent neurons) 1 is chosen. ...

So, I have a classifier which looks like clf = VotingClassifier(estimators=[ ('nn', MLPClassifier()), ('gboost', GradientBoostingClassifier()), ('lr', LogisticRegression()), ], voting='sof...

I applied SVM (scikit-learn) in some dataset and wanted to find the values of C and gamma that can give the best accuracy for the test set. I first fixed C to a some integer and then iterate over ...

I have a logistic regression model with a defined set of parameters (warm_start=True). As always, I call LogisticRegression.fit(X_train, y_train) and use the model after to predict new outcomes. ...

I'm trying to figure out how to built a workflow for sklearn.neighbors.KNeighborsRegressor that includes: normalize features feature selection (best subset of 20 numeric features, no specific tot...

I have found a set of best hyperparameters for my KNN estimator with Grid Search CV: >>> knn_gridsearch_model.best_params_ {'algorithm': 'auto', 'metric': 'manhattan', 'n_neighbors': 3} ...