Category "machine-learning"

Invocation timed out using Sagemaker to invoke endpoints with pretrained custom PyTorch model [Inference]

I have a pretrained model based on PyTorch (contextualized_topic_models) and have deployed it using AWS sagemaker script model. However, when I tried to invoke

When using padding in sequence models, is Keras validation accuracy valid/ reliable?

I have a group of non zero sequences with different lengths and I am using Keras LSTM to model these sequences. I use Keras Tokenizer to tokenize (tokens start

ImportError: No module named grid_search, learning_curve

Problem with Scikit learn l can't use learning_curve of Sklearn and sklearn.grid_search. When l do import sklearn (it works) from sklearn.cluster import biclus

How to set the parameters grids correctly when tuning the workflowset with tidymodels?

I try to use tidymodels to tune the workflow with recipe and model parameters. When tuning a single workflow there is no problem. But when tuning a workflowsets

ValueError: hist method requires numerical columns, nothing to plot

I was going through a tutorial, but as I was running the code in an IDE, an error occurred. The link to the tutorial is here: https://thecleverprogrammer.com/20

How to deal with overfitting of xgboost classifier?

I use xgboost to do a multi-class classification of spectrogram images(data link: automotive target classification). The class number is 5, training data includ

I Need Assistance to Interpret the Score as a means to decide on the best regressor for my ML model

I am working on a Model for Machine Learning and was able to generate the scores of the processes. I am not sure how to use them to make a decision on which is

Reshape the input for BatchDataset trained model

I trained my tensorflow model on images after convert it to BatchDataset IMG_size = 224 INPUT_SHAPE = [None, IMG_size, IMG_size, 3] # 4D input model.fit(

XGBoost giving a static prediction of "0.5" randomly

I am using a scikit-learn pipeline with XGBRegressor. Pipeline is working good without any error. When I am prediction with this pipeline, I am predicting the

How can we make use of feature variables whose future values are fixed to predict target value?

With regard to time series features in a regression ML model. Suppose, we are living in a space colony. The temperature there is accurately under control, so we

Does sklearn LogisticRegressionCV use all data for final model

I was wondering how the final model (i.e. decision boundary) of LogisticRegressionCV in sklearn was calculated. So say I have some Xdata and ylabels such that

A `Concatenate` layer requires inputs with matching shapes except for the concatenation axis. Received: input_shape=[(None, 28), (None, 28, 28)]

""" Defining two sets of inputs Input_A: input from the features Input_B: input from images my train_features has (792,192) shape my train_images has (792,28,28

How to compare dates in python and find the greater one

I want to compare 2 date and predict a label true if date 1 greater than date 2 and predict false date 1 less than date 2. I have trained the model but model is

How do I load a local model with torch.hub.load?

I need to avoid downloading the model from the web (due to restrictions on the machine installed). This works, but it downloads the model from the Internet mode

How to apply StandardScaler in Pipeline in scikit-learn (sklearn)?

In the example below, pipe = Pipeline([ ('scale', StandardScaler()), ('reduce_dims', PCA(n_components=4)), ('clf', SVC(kernel = 'linear

RandomForestClassifier instance not fitted yet. Call 'fit' with appropriate arguments before using this method

I am trying to train a decision tree model, save it, and then reload it when I need it later. However, I keep getting the following error: This DecisionTre

Use multiple time-series to train model

Is there any way to use multiple time-series to train one model and use this model for predictions given a new time-series as an input? It is rather a theoretic

Plot scikit-learn (sklearn) SVM decision boundary / surface

I am currently performing multi class SVM with linear kernel using python's scikit library. The sample training data and testing data are as given below: Mode

How do I remove nonsensical or incomplete words from a corpus?

I am using some text for some NLP analyses. I have cleaned the text taking steps to remove non-alphanumeric characters, blanks, duplicate words and stopwords, a

For loop in Label encoding and one hot encoder

My Data set contains categorical variables so I am using label encoding and one hot encoder and my code is as follows can I use a loop to ensure that my cod