Heartbeat

SEPTEMBER 13, 2023

Through the explainability of AI systems, it becomes easier to build trust, ensure accountability, and enable humans to comprehend and validate the decisions made by these models. For example, explainability is crucial if a healthcare professional uses a deep learning model for medical diagnoses. References Castillo, D.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Mlearning.ai

FEBRUARY 15, 2023

Some important things that were considered during these selections were: Random Forest : The ultimate feature importance in a Random forest is the average of all decision tree feature importance. A random forest is an ensemble classifier that makes predictions using a variety of decision trees. Cambridge: MIT Press.

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

DrivenData Labs

MAY 1, 2025

Solvers used 2016 demographics, economic circumstances, migration, physical limitations, self-reported health, and lifestyle behaviors to predict a composite cognitive function score in 2021. Summary of approach: I used LightGBM decision tree algorithm to predict the difference between test participants scores from different years.

Decision Trees 147

Decision Trees Clustering Algorithm Machine Learning 147