A.I, Data and Software Engineering

Search results forclassification

Metrics for regression and classification – quick note

In this article, we review some common metrics and their uses for two main ML problems, i.e. regression and classification. Regression Metrics Most of the blogs have focussed on classification metrics like precision, recall, AUC etc. For a change, I wanted to explore all kinds of metrics including those used in regression as well. MAE and RMSE are the two most popular metrics for continuous...

squared hinge loss

Petamind A.I

The squared hinge loss is a loss function used for “maximum margin” binary classification problems. Mathematically it is defined as: where ŷ the predicted value and y is either 1 or -1. Thus, the squared hinge loss is: 0* when the true and predicted labels are the same and* when ŷ≥ 1 (which is an indication that the classifier is sure that it’s the correct label)quadratically increasing with the...

Decision Tree Regression quick note

Petamind A.I

Decision tree builds regression or classification models in the form of a tree structure. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes. A decision node (e.g., Outlook) has two or more branches (e.g., Sunny, Overcast and Rainy), each representing...

MLP for implicit binary collaborative filtering

multi-layer perception

In this post, we demonstrate Keras implementation of the implicit collaborative filtering. We also introduce some techniques to improve the performance of the current model, including weight initialization, dynamic learning rate, early stopping callback etc. The implicit data For demonstration purposes, we use the dataset generated from negative samples using the technique mentioned in this post...

Predict coronavirus deaths by days

As the pandemic is going on with an increasing number of deaths daily, let create a simple model to predict the deaths caused by 2019-nCoV (Wuhan Coronavirus). The 2019-nCoV death data I grab the death toll data from World Meters website. DateDaily DeathsFeb. 889Feb. 786……Jan. 2416Jan. 238 Plot the data Firstly, we transform the table into a Pandas data frame. 123 death_toll =...

A.I, Data and Software Engineering

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