TAG: classification

The data has been produced using Monte Carlo simulations. The first 21 features (columns 2-22) are kinematic properties measured by the particle detectors in the accelerator. The last seven features are functions of the first 21 features; these are high-level features derived by physicists to help discriminate between the two classes. There is an interest […]

Learn the basics of classification with with the more popular example, the Iris dataset.

The two datasets are related to red and white variants of the Portuguese “Vinho Verde” wine. Due to privacy and logistic issues, only physicochemical (inputs) and sensory (the output) variables are available (e.g. there is no data about grape types, wine brand, wine selling price, etc.)

Our case study is a bank that wants to develop a churn model to predict the probability of a customer to churn. The banking sector has become one of the main industries in developed countries. The technical progress and the increasing number of banks raised the level of competition. Banks are working hard to survive […]

Data from IBM Watson tutorials.

Predict if a new client is going to get a loan or not based on historical data.

Dataset for predicting forest cover types from cartographic variables.

The palmerpenguins data contains size measurements for three penguin species observed on three islands in the Palmer Archipelago, Antarctica.

The aim is to find whether or not a person has heart disease based on information about their health.

Let´s prepare a simple example where we can verify that Dataslayer ML learns from a predefined data logic. The ML will discover this logic.