Random Forests are awesome. They do not overfit, they are easy to tune, they tell you about important variables, they can be used for classification and regression, they are implemented in many programming languages and they are faster than their competitors (neural nets, boosting, support vector machines, ...)Let us take a moment to appreciate them:The Random Forest™ is my shepherd; I shall not want. He makes me watch the mean squared…
The role of context in statistical analysis The wonderful advantage of teaching statistics is the real-life context within which any applicaton must exist. This can also be one of the difficulties. Statistics without context is merely the mathematics of statistics, … Continue reading →
The Lakers recently snapped a four game losing streak. In that game Kobe, the league leader in field goal attempts and missed shots, had a season low of 14 points but a season high of 14 assists. This makes sense … Continue reading →
Currently a lot of people are talking about the new shiny package. So I got curious and built an own, more or less useful app: A drink trackerThis app can be used to track how much someone drank and therefore it is very useful for every party, especial...
