What is Tree-Based Models ?

What are Tree-Based Models?

Tree-based models are a kind of supervised learning method that is helpful for both classification and regression tasks. They function by dividing the data into groups based on the value of input features, building a tree-shaped diagram of choices. Well-known examples include Decision Trees, Random Forests, and Gradient Boosting Machines. Breiman et al. (1984) introduced the idea of classification and regression trees (CART), which are the foundation of many tree-based models used today.

Why are Tree-Based Models Important?

• Interpretability: Tree-based models are often simpler to understand when compared to other machine learning algorithms. You can see and understand the decision path from the root to the leaf, which is helpful in areas where you need to explain how things work.
• Handling Non-Linear Relationships: These models are good at dealing with complex non-linear connections between input features and the target variable, a task that linear models find hard.
• Robustness to Outliers: Tree-based models are strong against outliers and not important features, which improves their ability to predict well.

What are the Benefits of Tree-Based Models?

• Versatility: They serve many predictive modeling needs, from classifying, estimating, to ranking.
• Feature Importance: Models based on trees help reveal what features matter most in predicting the outcome assisting with choosing and forming features.
• Scalability: Techniques such as Random Forest and Gradient Boosting scale well and manage big datasets fitting them for large data tasks.

How Alltius AI Enables Organizations to reduce tree-based models?

Alltius' provides leading enterprise AI technology for enterprises and governments to harness and extract value from their current data using variety of technologies. Alltius' Gen AI platform enables companies to create, train, deploy and maintain AI assistants for sales, support agents and customers in a matter of a day. Alltius platform is based on 20+ years of experience at leading researchers at Wharton, Carnegie Mellon and University of California and excels in improving customer experience at scale using Gen AI assistants catered to customer's needs. Alltius' successful projects included but are not limited to Insurance(Assurance IQ), SaaS (Matchbook), Banks, Digital Lenders, Financial Services (AngelOne) and Industrial sector(Tacit).

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