Artley

Why cubic splines are the best regression model out there.Cubic Spline Intro — By AuthorIntroductionIn this article, I will go through cubic splines and show how they are more robust than high degree linear regression models. First I will walk through the mathematics behind cubic splines, then I will show the model in Python, and finally, I will explain Runge’s phenomenon.The python library used in this article is called Regressio. This is an open source python library created by the author for univariate regression,…

Showcasing the power of ensemble learning with decision trees and ARIMA modelsMeter Image — By Doris MorganIn this article, I am going to showcase the predictive power of ensemble learning for time series forecasting. Ensemble learning leads to models with higher predictive accuracy, a lower likelihood of overfitting, and a diverse set of predictions.I will be using a dataset provided by ASHRAE (The American Society of Heating, Refrigerating and Air-Conditioning Engineers) which has hourly meterage data on electricity,…

The fastest and most intuitive unsupervised clustering algorithm.Clusters Image — By AuthorIn this article, we will go through the k-means clustering algorithm. We will first start looking at how the algorithm works, then we will implement it using NumPy, and finally, we will look at implementing it using Scikit-learn.K-means clustering is an unsupervised algorithm that groups unlabelled data into different clusters. The K in its title represents the number of clusters that will be created. This is something that should…

An introduction to the mathematics behind neural networksNetwork Image — By Clint AdairIntroductionIn this article, we will go through the mathematics behind training a simple neural network that solves a regression problem. We will use an input variable x to predict an output variable y. We will train two models by hand and then train a final model using Python.Before starting, it would be good to know a little multivariate calculus, linear algebra, and linear regression to fully understand the mathematical processes…

Estimate the range of a future observation with confidenceTarget Image — By Afif KusumaForecasting in the real world is an important task. Consider forecasting energy demand, temperature, food supply, and health indicators just to name a few. Getting an inaccurate forecast in these cases can have a significant impact on people’s lives.This is where prediction intervals can help. Prediction intervals are used to provide a range where the forecast is likely to be with a specific degree of confidence. For example, if you…

The most important, overlooked, and predictable regression model.Linear Regression Image — By AuthorLinear regression is a simple, yet powerful tool that should be in every data scientist’s back pocket. In this article, I will use a real-world example to showcase the power of linear regression on real-world data.CalCOFI DatasetWe are going to be working with the CalCOFI Dataset. This dataset contains comprehensive oceanographic measurement data from California from 1949 up to the present day. The dataset includes features…