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Random Decision Forests

Here you’ll find everything about decision forests, whether it’s tutorials on implementing decision forests in Python or tuning them with random search. 

Decision forests belong to the class of ensemble models. The idea of a Random Forest is to use sets of decision trees instead of individual trees. Finding the right parameters of a decision forest can be challenging or time-consuming using the right optimization technique. Common methods for generating suitable forests are boosting or bagging. Moreover, in practice, a decision forest may have several hundred decision trees. Therefore, decision forests are less transparent in how they make decisions than single decision tree models. Nevertheless, decision forests are widely used because they often achieve excellent performance.

Feature Engineering and Selection for Regression Models with Python and Scikit-learn

March 6, 2023September 26, 2022
car price prediction machine learning tutorial python-min

Training a machine learning model is like baking a cake: the quality of the end result depends on the ingredients … Read more

Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python

March 10, 2023April 7, 2022

Finding the perfect hyperparameters for your machine learning model can be like searching for a needle in a haystack – … Read more

Measuring Machine Learning Classifier Performance with Python and Scikit-Learn

March 6, 2023December 31, 2021
Measuring Classification Performance Medical Machine Learning midjourney relataly

Have you ever received a spam email and wondered how your email provider was able to identify it as spam? … Read more

Predictive Policing: Preventing Crime in San Francisco using XGBoost and Python

February 27, 2023March 7, 2021
san francisco crime map python machine learning crime type prediction-min

In this tutorial, we’ll be using machine learning to predict and map out crime in San Francisco. We’ll be working … Read more

Customer Churn Prediction – Understanding Models with Feature Permutation Importance using Python

December 27, 2022August 2, 2020
churn prediction python

One of the primary goals of many service companies is to build solid and long-lasting relationships with their customers. Customers … Read more

Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python

February 27, 2023July 6, 2020
hyperparameter tuning titanic dataset machine learning

Are you looking to optimize the hyperparameters of a machine learning model using Python’s Scikit-learn library? Look no further! In … Read more

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