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DNI Institute Blogs

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Support Vector Machine: Overview

Support Vector Machine (SVM) is one of the machine learning algorithms used for supervised problem sets mainly. Some of the other algorithms which can be explored along with SVM are Decision Tree, Random Forest, Neural Network, or Logistic Regression, specifically for Binary Classification problems. Due to the mathematical complexity involved …

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Deep Neural Network for Structured

Preventive and predictive methods can help in managing the devastating effect of heart diseases. In this blog, we aim to show simple steps involved in building a predictive model using the Deep Neural Network method to predict a heart attack. A detailed overview of Heart Attack Prediction has been discussed …

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Test of Association for Categorical1

A T-test is often used when you want to compare whether two groups of data are significantly different from each other. We do this by comparing the means of the two different groups. For example, whether patients who received medication have higher T-cell counts compared to patients who didn't or …

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Market Basket Analysis - Step by step approach

The objective is to explain the steps involved in Market Basket Analysis (MBA) or Association Analysis. Also, explain the key terminologies used. We will leverage customer transaction data for developing association rules & insights which can be used for right product bundling and promotions, assortment planning and inventory management, and …

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Confusion Matrix and Cost Matrix

One of the commonly used model performance assessment tools is a confusion matrix. It compares actual labels vs predicted labels and allows us to measure accuracy, the ratio of correct predictions to the total number of predictions, and a few other measures such as precision, recall, etc. A cost matrix …

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Test of Association for Categorical Variables

A T-test is often used when you want to compare whether two groups of data are significantly different from each other. We do this by comparing the means of the two different groups. For example, whether patients who received medication have higher T-cell counts compared to patients who didn't or …

Read More