Random projection trees
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Updated
Nov 4, 2021 - Haskell
Random projection trees
The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset
Built for the implementation of Keras in Tensorflow. Behaves similarly to GridSearchCV and RandomizedSearchCV in Sci-Kit learn, but allows for progress to be saved between folds and for fitting and scoring folds in parallel.
Various Regression models including linear, polynomial, ridge, lasso and elastic net were experimented with to find which model best predicted health insurance costs. The models were evaluated using cross-validation, from which the best models were optimized using randomized search. The best model was then evaluated on the test data.
Compare time complexity of binary search algorithm and randomized search algorithm to search for 1000 keys in a sorted array
Bank Credit Card Customer churn prediction
Personal notes for modern optimization methods course (University of Edinburgh 2017-1)
Nine Mens Morris (Human vs AI) implemented in Python by using Alpha–Beta Pruning algorithm and Randomized Search Heuristics.
Прогнозирование рыночной стоимости автомобилей
Email spam classification for Naive Bayes, Gradient Boosting Machine, Support Vector Machine and Random Forest
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