## Offset and Weights in GLM Regression

Introduction In GLMs, we often encounter scenarios where we need to account for exposure or adjust for certain factors. Both offset and weights play crucial roles in achieving this. Letâ€™s …

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# Category: Fundamentals

## Offset and Weights in GLM Regression

## Frequency-Severity Modeling in consideration of COVID-19 induced effects

## Non-Linear Classification Methods in Spark

## Kubernetes at an OrangePi

## Solving the Multiarmed Bandit problem with JavaScript

## An introduction to the Registration Problem

## Non-Linear Support Vector Machines (SVM)

## Fourier Transform

A science blog about my spare time data analysis projects.

Introduction In GLMs, we often encounter scenarios where we need to account for exposure or adjust for certain factors. Both offset and weights play crucial roles in achieving this. Letâ€™s …

This post is supposed to give a brief introduction in Frequency-Severity models. These models are very popular for determine the optimal price for an insurance. We will take a look …

In a previous post I covered how to apply classical linear estimators like support vector machines or logistic regression to a non-linear dataset using the kernel method. This article can …

1. Install k3s at the OrangePI In a previous article I explained how to get spark running at an OrangePi to create a toy computing-cluster. If you look at this …

1. Formulation of the Multiarmed Bandit Problem Consider the following problem: A gambler enters a casino with slot machines. The probability to receive a reward for each slot machine follows …

To explain the registration problem i will start with an example. In Figure 1 the pinch force dataset is shown, to collect the data a group of 20 subjects were …

1. Introduction This blog post is about Support Vector Machines (SVM), but not only about SVMs. SVMs belong to the class of classification algorithms and are used to separate one …

1. The Fourier Transform The Fourier transform of an integrable function with is given by (1) Under suitable conditions, the inverse transform from to with is then given by …