Byte
Regression is a technique in statistics and machine learning, in which the value of an independent variable is predicted by its relationship with other variables. Frameworks like Scikit-Learn make it easier than ever to perform regression with a wide variety of models - one of the strongest ones being built...
David Landup
Regression is a technique in statistics and machine learning, in which the value of an independent variable is predicted by its relationship with other variables. Frameworks like Scikit-Learn and XGBoost make it easier than ever to perform regression with a wide variety of models - one of the recently well-adopted...
Scikit-Learn's scalers are the backbone of practically all regressors and classifiers built on top of them, scaling the data to a workable range and preparing a latent representation to learn from. If you'd like to read more about feature scaling, read our "Feature Scaling Data with Scikit-Learn for Machine...
RandomizedSearchCV and GridSearchCV allow you to perform hyperparameter tuning with Scikit-Learn, where the former searches randomly through some configurations (dictated by n_iter) while the latter searches through all of them. XGBoost is an increasingly dominant library, whose regressors and classifiers are doing wonders over more traditional implementations, and is...
XGBoost is gaining a lot of traction, and its downloads are increasing. Yet, there's a common issue with the installation, especially in Jupyter Notebook environments where it's typically installed with: ! pip install xgboost # Or ! pip3 install xgboost # Or ! conda install -c conda-forge xgboost Oftentimes, even though this approach works for...
Saving and loading Scikit-Learn models is part of the lifecycle of most models - typically, you'll train them in one runtime and serve them in another. In this Byte - you'll learn how to save and load a regressor using Scikit-Learn. First off, let's build a simple regressor and fit...
So - you've trained a sparkling regressor using XGBoost! Which features are the most important in the regression calculation? The first step in unboxing the black-box system that a machine learning model can be is to inspect the features and their importance in the regression. Let's quickly train a mock...
In many programming languages, underscores are used to separate words, which is called snake case (i.e. snake_case). This is especially true in Python, which can use underscores to separate module names, function names, and variable names. You've probably encountered this format in other areas as well, like in...
Scott Robinson
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