bias-variance-tradeoff
There are 24 repositories under bias-variance-tradeoff topic.
csinva/mdl-complexity
MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
Amitha353/Machine-Learning-Regression
Machine-Learning-Regression
Escapist-007/ML_Projects
The projects are part of the graduate-level course CSE-574 : Introduction to Machine Learning [Spring 2019 @ UB_SUNY] . . . Course Instructor : Mingchen Gao (https://cse.buffalo.edu/~mgao8/)
HolmesShuan/Bias-Variance-Decomposition-for-KL-Divergence
This repository includes some detailed proofs of "Bias Variance Decomposition for KL Divergence".
aroques/bias-variance
Bias variance experiment from Learning from Data. Problem 2.24, p. 75.
bhattbhavesh91/bias_variance_example
This is a simple python example to demonstrate bias variance
QuanHoangNgoc/Bias-Variance-Tradeoff-CS115-Math4CS-
The Bias-Variance Tradeoff Visualization project provides an interactive tool to understand the bias-variance tradeoff in machine learning models. It visually demonstrates how different models perform on training and validation datasets, helping users grasp the concepts of overfitting and underfitting.
AntonMu/BiasVarianceTradeoff
Explanation of the Bias Variance Tradeoff in Machine Learning
fardinabbasi/Linear_Regression
Performing polynomial regression of varying degrees on data affected by white and Poisson noise, evaluating the model performance based on MSE loss and the bias-variance trade-off.
junwu6/FedBVA
Adversarial Robustness through Bias Variance Decomposition: A New Perspective for Federated Learning
ayushsharma-crypto/Bias-Variance-Tradeoff
A python code for demonstration of Bias-Variance TradeOff concept in Machine Learning
LorenzoCastiglia/Deep-Learning-for-Image-Classifiaction
Deep Learning project about the design and training of a model for Image Classification
mark-antal-csizmadia/slp-mlp
Single Layer Perceptrons (SLPs) and Multi-Layer Perceptrons (MLPs) from scratch, only with numpy, for classification and regression. MLPs with Keras for time-series prediction.
sancharee/HousePricePrediction
Hyparameter Tuning for identifying the most significant variables that influence House Prices
Taabannn/intro-ml
This repository has been created just for warm-up in machine learning and there are my simulation files of UT-ML course HWs.
AnneQuinkenstein/AccidentsInBerlin
Mithilfe von Machine Learning und Open Data zu Unfällen in Berlin (2018-2021) beantworten wir folgende Frage: Was sind die wichtigen Faktoren/Einflüsse auf Unfallgefahr? Und wie gut lässt sich damit die Unfallschwere überhaupt vorhersagen?
GregMurray30/machine_learning
Machine Learning programs in R
KyriakosPsa/Regression-from-scratch
This repository contains a generalized regression analysis problem solved from scratch, using only the Numpy library.
narenakash/Machine-Data-and-Learning
TLDR: Generic Algorithms, Decision Trees, Value Iteration, POMDPs, Bias-Variance. Data preprocessing using statistical techniques and visualization is crucial to understand and analyze the data before utilizing them to train a machine learning model. Several fundamental techniques for preprocessing are presented here.
oelin/parametric-complexity
Estimating the parametric complexity (minimum description length) of binary classifiers.
samiksha-khare/machine-learning
This project focuses on developing and training supervised learning models for prediction and classification tasks, covering linear and logistic regression (using NumPy & scikit-learn), neural networks (with TensorFlow) for binary and multi-class classification, and decision trees along with ensemble methods like random forests and boosted trees
sid230798/Regularization_Bias_Variance_Andrew_NG
Bias and Variance Tradeoff for debugging