Statistics

, we'll implement AUC in Excel. AUC is normally used for classification tasks as a performance metric. But we start with a confusion matrix, because that's where everyone begins in practice. Then we'll see why a...

Introduction customer annoyance from wait times. Calls arrive randomly, so wait time X follows an Exponential distribution—most waits are short, just a few are painfully long. Now I’d argue that annoyance isn’t linear: a 10-minute...

, we ensemble learning with voting, bagging and Random Forest. Voting itself is simply an aggregation mechanism. It doesn't create diversity, but combines predictions from already different models.Bagging, however, explicitly creates diversity by training...

For 18 days, we've got explored many of the core machine learning models, organized into three major families: distance- and density-based models, tree- or rule-based models, and weight-based models. Up so far, each article focused...

this text, I’ll show you learn how to use two popular Python libraries to perform some geospatial evaluation of traffic accident data inside the UK. I used to be a comparatively early adopter of...

With Logistic Regression, we learned classify into two classes. Now, what happens if there are greater than two classes. n is just the multiclass extension of this concept. And we are going to discuss this...

Today’s model is Logistic Regression. In the event you already know this model, here is an issue for you: Is Logistic Regression a regressor or a classifier? Well, this query is precisely like: Is a tomato a...

with Decision Trees, each for Regression and Classification, we are going to proceed to make use of the principle of Decision Trees today. And this time, we're in unsupervised learning, so there aren't any...