As stated in the title, I’m confused by the k-folding approach in GridSearchCV which allows you to specify its cv attribute as the number of folds. Howeve
I am trying to build a classification model, but I don't have enough data. What would be the most appropriate way to create synthetic data based on my existing
I'd like to create class labels for a permutation of two columns using sklearn's LabelEncoder(). How do I achieve the following behavior? import pandas as pd im
Output- "ValueError: could not convert string to float: 'Private Sector/Self Employed' ". I need help with this error as I get this error consistently import nu
Is it possible to mix small datatypes (such as bits) and long datatypes (such as 256-bit hashes) when using a machine learning model in scikit-learn such as the
Could someone explain why this code: from sklearn.model_selection import train_test_split import pandas as pd from sklearn.model_selection import StratifiedKFol
so I've been developing some machine learning models using sklearn and tensorflow in python . and I want to integrate it into a java web app. so far I've been s
Is there a way to convert back and forth between a binary vector and a 128-bit number? I have the following binary vector: import numpy as np bits = np.array([
I want to generate a synthetic data from scratch which is a binary outcome sequence data (0/1). My data has following property- For the sake of an example, lets
I'm trying to use the yellowbrick PredictionError and am running into strange dimensionality issues. I am using yellowbrick version 1.4. Suppose we had this ver
I am trying to build a model to predict house prices. I have some features X (no. of bathrooms , etc.) and target Y (ranging around $300,000 to $800,000) I have
I have the following vectors in my toy example: data = pd.DataFrame({ 'id': [1, 2, 3, 4, 5], 'a': [55, 2123, -19.3, 9, -8],
prediction_class = labelencoder.inverse_transform(predicted_label) prediction_class ValueError: y should be a 1d array, got an array of shape (1, 10) instead. p
I'm getting this error:Collecting scikit-learn==0.21.3 Using cached scikit-learn-0.21.3.tar.gz (12.2 MB) Requirement already satisfied: numpy>=1.11.0 in c:\u
I tried to implement formula from Wikipedia but results are different. Why is it so? y_true = np.array([1, 1, 0]) y_pred = np.array([1, 0, 1]) r2 = r2_score(y_
I need a TF-IDF value for a word that is found in number of documents and not only a single document or a specific document. For example, Consider this corpus c
Does anyone know how to convert a .csv file to a .data or know how to use only half of a .data file like a csv file? I'm trying to achieve a mean Average Positi
I have a major problem with XAI, Shap, Lime you name it in general. Here is a basic example for shap. My problem is that when I use a real tuned model, which is
I have a major problem with XAI, Shap, Lime you name it in general. Here is a basic example for shap. My problem is that when I use a real tuned model, which is
I have a complex system with a lot of parameters, each parameter interact with others. I could have some parameters values of this system at one time ("a", "b",