The combined classifier algorithm is a commonly used technique, which is implemented by creating a voting system. Each algorithm has…

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## Machine learning with the “diabetes” data set in R

Machine learning with the “diabetes” data set in RClassification with KNN, logistic regression, and decision treesWilliam ButlerBlockedUnblockFollowFollowingJan 17Inspired by Susan Li’s article…

Continue Reading## Logistic Regression Model Tuning with scikit-learn — Part 1

Logistic Regression Model Tuning with scikit-learn — Part 1Comparison of metrics along the model tuning processFinn QiaoBlockedUnblockFollowFollowingJan 8Classifiers are a core component of machine…

Continue Reading## Impact of Dataset Size on Deep Learning Model Skill And Performance Estimates

We will define a model that performs well on this dataset as a model that has effectively learned the two…

Continue Reading## How to Reduce the Variance of Deep Learning Models in Keras Using Model Averaging Ensembles

The model then has a single hidden layer with 15 modes and a rectified linear activation function, then an output…

Continue Reading## Text Generation Using Recurrent Neural Networks

It has an average accuracy of 0.6245 and loss of 1.25 over 5 randomly sampled test sequences.Yes, but to talk…

Continue Reading## A Guide for Building Convolutional Neural Networks

Before that, you’re just experimenting and prototyping and so there’s no need to make your training time longer by having…

Continue Reading## How I improved a Human Action Classifier to 80% Validation Accuracy in 6 Easy Steps

The ensemble achieved a validation accuracy of 0.821 which is a significant improvement from the baseline paper’s accuracy of 0.672.Background…

Continue Reading## Holy Grail of AI for Enterprise — Explainable AI

In reality, Customers are the less bothered accuracy of AI model, but their concerns are about Cluelessness of Data Scientist…

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