However, in favor of our proposal, it can be noted that, in most cases, the performances of the 3-SBC classifier do not vary overly from the high balanced accuracy values obtained by other classifiers ...
Moving cannabis to a category of drugs that includes some common medicines will have implications for research, businesses and patients. By Jan Hoffman President Trump on Thursday ordered cannabis to ...
In an era of rapidly growing multimedia data, the need for robust and efficient classification systems has become critical, specifically the identification of class names and poses or styles. This ...
An interactive SMS Spam Detection application using Streamlit and machine learning. This app allows users to classify messages as spam or ham and view performance metrics for different models. A SMS ...
Abstract: Diabetes Mellitus is one of the chronic diseases with a prevalence that is increasing globally. Data from the World Health Organization (WHO) shows that the number of Diabetes Mellitus cases ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other ...
The goal of a machine learning regression problem is to predict a single numeric value. There are roughly a dozen different regression techniques such as basic linear regression, k-nearest neighbors ...
Using the Sklearn classifiers: Naive Bayes, Random Forest, Adaboost, Gradient Boost, Logistic Regression and Decision Tree good success rates are observed in a very simple manner. In this work ...
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