I am using this code to detect face_spoofing import numpy as np import cv2 import joblib from face_detector import get_face_detector, find_faces def calc_hist(
I have tried this according to this awnser x = df[feature_collums] y = df[[label_column]][label_column] from sklearn.preprocessing import MinMaxScaler scaler =
I want to perform a random search, in classification problem, where the scoring method will be chosen as AUC instead of accuracy score. Have a look at my code f
I want to use StandardScaler only on certain columns, however my code resulted in error. Here is my code: from sklearn.preprocessing import StandardScaler num_c
I am training a computer vision model. I divide the images in 3 datasets: training, validation and testing. So that I get always the same images in training, va
As an example, suppose there is a random forest and a logistic regression model that accept the same input data, and I want the inference result to be the avera
I'm following the book Hands-on Machichine Learning by Aurelien Geron, more specifically, where it begins to go into classifiers. I'm following the code from th
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
I am trying install scipy in FreeBSD 13. I have built python 3.10 on FreebSD 13 and managed to install pandas, matplotlib and numpy on a virtual environment whi
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 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'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 am trying to identify the important features in a data frame containing stock data. I plan on using LSTM to predict closing prices later on. I currently have
I want to create a sklearn pipeline that consists of two steps: Custom transformer function Keras classification model This is my data set (of course, I'm provi
I am running different machine learning models on my data set. I am using sklearn pipelines to try different transforms on the numeric features to evaluate if o
I have a dozen pre-trained DNNs that I wish to add to a sklearn ensemble. The issue is that it seems I can not provide pre-trained models to KerasClassifier. cl
I'm building a chain classifier for a multiclass problem that uses Keras binary Classifier model in a chain. I have 17 labels as classification target and datas
There is a proposal to implement this in Sklearn #15075, but in the meantime, eli5 is suggested as a solution. However, I'm not sure if I'm using it the right w
I have a list of models that I iterate through in a for loop getting their performances. I've added catboost to my model list, but when I try to add it's best e
I am using GridSearchCV() and its fit() method to build a model. I currently have this working, but would like to improve the accuracy of the model by supplying