"Reading Data" is a series on Python and machine learning for clinicians and medical researchers. We start by acquiring programming skills to build the ability to "read and interpret" your own data.

Linear Trees combine the learning ability of Decision Tree with the predictive and explicative power of Linear Models. Like in tree-based algorithms, the data are split according to simple decision ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. With the rapid growth of artificial intelligence and machine learning across ...

Sales data covers a wide range of information, including customer details, sales figures, and marketing data. The first step is to collect this data and preprocess it appropriately. Extract data from ...

Stocks in the Chinese stock market can be divided into ST stocks and normal stocks, so to prevent investors from buying potential ST stocks, this paper first performs SMOTEENN oversampling data ...

With major code and visualization clean up contributions done by Matthew Epland (@mepland). To interopt with these different libraries, dtreeviz uses an adaptor object, obtained from function dtreeviz ...

Parkinson's Disease (PD) is the second most common age-related neurological disorder that leads to a range of motor and cognitive symptoms. A PD diagnosis is difficult since its symptoms are quite ...

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...