Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

xkcd #2048 is exceptionally relevant to this. Doing linear regression well with a big dataset is difficult! I do this all the time at work and honestly I often show a scatter plot without any ...

Learn what is Linear Regression Cost Function in Machine Learning and how it is used. Linear Regression Cost function in Machine Learning is "error" representation between actual value and model ...

Abstract: In the traditional graph embedding framework, the graph is usually built by k-NN or r-ball. Since it is difficult to manually set the parameters k and r in the high-dimensional space, sparse ...

Abstract: At present, Symmetric Positive Definite (SPD) matrix data is the most common non-Euclidean data in machine learning. Because SPD data don’t form a linear space, most machine learning ...

The linear model is a modelling workhorse for data analyses commonly referred to in the social and behavioural sciences as regression analysis and is an essential building block towards more advanced ...

In order to adjust the models for predicting soil property results from the pXRF data, two methods were tested: stepwise multiple linear regression (SMLR) and random forest algorithm (RF). The SMLR ...