An open API service providing repository metadata for many open source software ecosystems.

Topic: "boosting-tree"

cerlymarco/linear-tree

A python library to build Model Trees with Linear Models at the leaves.

Language: Jupyter Notebook - Size: 5.92 MB - Last synced at: 6 months ago - Pushed at: 9 months ago - Stars: 355 - Forks: 54

rosetta-ai/rosetta_recsys2019

The 4th Place Solution to the 2019 ACM Recsys Challenge by Team RosettaAI

Language: Python - Size: 161 KB - Last synced at: 5 months ago - Pushed at: over 5 years ago - Stars: 58 - Forks: 16

adelekuzmiakova/CS229-machine-learning-solar-energy-predictions

Predicting solar energy using machine learning (LSTM, PCA, boosting). This is our CS 229 project from autumn 2017. Report and poster are included.

Language: Python - Size: 922 MB - Last synced at: about 1 year ago - Pushed at: almost 4 years ago - Stars: 48 - Forks: 12

yubin-park/bonsai-dt

Programmable Decision Tree Framework

Language: Python - Size: 3.81 MB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 34 - Forks: 6

kongzii/SwiftXGBoost

Swift wrapper for XGBoost gradient boosting machine learning framework with Numpy and TensorFlow support.

Language: Swift - Size: 5.29 MB - Last synced at: 10 days ago - Pushed at: over 4 years ago - Stars: 26 - Forks: 1

NaoMatch/FortLearner

Machine Learning Algorithms in Fortran

Language: Fortran - Size: 13.6 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 23 - Forks: 2

xiaodaigh/JLBoostMLJ.jl 📦

MLJ.jl interface for JLBoost.jl

Language: Julia - Size: 51.8 KB - Last synced at: 3 months ago - Pushed at: about 4 years ago - Stars: 9 - Forks: 0

karthik-d/FungiCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

Language: Python - Size: 15.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 2

prs98/Telecom_Churn_Analysis

This project focuses on segmenting customers based on their tenure, creating "cohorts", allowing us to examine differences between customer cohort segments and determine the best tree based ML model.

Language: Jupyter Notebook - Size: 7.57 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 2

karthik-d/SnakeCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in SnakeCLEF-2022, part of the 13th CLEF Conference, 2022

Language: Python - Size: 11.9 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 2

GINK03/bing-ranking-inspector

Microsoft Bingのランキングの重みを自然言語的に解釈、表現します

Language: Python - Size: 22.8 MB - Last synced at: over 1 year ago - Pushed at: about 7 years ago - Stars: 1 - Forks: 1

newking9088/building_insurance_predictive_modeling

A comprehensive case study on implementing predictive modeling in insurance

Size: 713 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 0 - Forks: 1

jodhie/building_insurance_predictive_modeling

A comprehensive case study on implementing predictive modeling in insurance

Size: 173 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

Szymon-Czuszek/Machine-Learning-Algorithms

In this repository, I will share the materials related to machine learning algorithms, as I enrich my knowledge in this field.

Language: Jupyter Notebook - Size: 2.52 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

svsaurav95/Zepto-analysis-

Zepto Order Analysis to Predict Unique Orders from a range of Products

Language: Jupyter Notebook - Size: 3.91 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

DanielaRosero/Gradient-Boosting-Classifier-for-Wine-Classification

Use of Weights & Biases to systematically tune and evaluate the hyperparameters of a Gradient Boosting Classifier. The dataset we are working with is the Wine dataset.

Language: Jupyter Notebook - Size: 1010 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

unnatibshah/LASSO-and-Boosting-for-Regression

LASSO and Boosting for Regression on Communities and Crime data

Language: Jupyter Notebook - Size: 8.82 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

sheny2/Cloud_Detection

classfication of cloud image pixels

Language: R - Size: 1.05 GB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 1

JQmiracle/HR_Analytics

Job Change of Data Scientists Prediction

Size: 6.31 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0

gt0410/Unredactor

In this project we are tryinbg to create unredactor. Unredactor will take a redacted document and the redacted flag as input, inreturn it will give the most likely candidates to fill in redacted location. In this project we are only considered about unredacting names only. The data that we are considering is imdb data set with many review files. These files are used to buils corpora for finding tfidf score. Few files are used to train and in these files names are redacted and written into redacted folder. These redacted files are used for testing and different classification models are built to predict the probabilies of each class. Top 5 classes i.e names similar to the test features are written at the end of text in unreddacted foleder.

Language: Python - Size: 8.71 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 1

srikanth2102/IPL_SCORE_PREDICTION

This project focuses on predicting the IPL scores using Machine learning models with the use of Python using Scikit Learn Library. The model predicts the score after a minimum of 5 overs. The score on Testing data was 94.17%.

Language: Jupyter Notebook - Size: 70.3 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

shreyash2610/-A-Fine-Windy-Day-HackerEarth

Problem Moving from traditional energy plans powered by fossils fuels to unlimited renewable energy subscriptions allows for instant access to clean energy without heavy investment in infrastructure like solar panels, for example. One clean energy source that has been gaining popularity around the world is wind turbines. Turbines are massive structures that are strategically placed in perpetually windy places to generate the most energy. Wind energy is generated when the power of the atmosphere’s airflow is harnessed to create electricity. Wind turbines do this by capturing the kinetic energy of the wind. Factors such as temperature, wind direction, turbine status, weather, blade length, etc. influence the amount of power generated.

Language: Jupyter Notebook - Size: 7.08 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0

rupalshrivastava/Supervised-Machine-Learning

Implemented support vector machines, boosting, and decision trees for classification problems. Used cross-validation for improving model accuracy. Plotted different types of learning curves like error rates vs train data size, error rates vs clock time. Compared performance using learning curves and confusion matrices across algorithms.

Language: Jupyter Notebook - Size: 1.16 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

AshwilNambiar/Datascience

Datascience hands on code

Language: Jupyter Notebook - Size: 3.79 MB - Last synced at: about 1 year ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

jdebran/KC_Practica_Machine-Learning-101

KeepCoding Bootcamp Big Data & Machine Learning - Práctica Machine Learning 101

Language: Jupyter Notebook - Size: 2.16 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

Amoko/Classification-based-on-Hierarchy-Rule-Tree

gene classification based on partial-order rule mining

Language: Python - Size: 28.3 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 0 - Forks: 0

Related Topics
machine-learning 18 random-forest 9 xgboost 6 decision-trees 5 deep-learning 5 linear-regression 4 logistic-regression 4 machine-learning-algorithms 4 boosting-algorithms 3 decision-tree 3 feature-selection 3 tensorflow 3 boosting-ensemble 2 risk-analysis 2 regulatory-compliance 2 modelvalidation 2 modeldeployment 2 decision-tree-classifier 2 clef 2 gradient-boosting-classifier 2 imageclef 2 keras 2 regression 2 xgboost-classifier 2 linear-models 2 multivariate-regression 2 python 2 neural-network 2 artificial-intelligence 2 data-science 2 ranking 2 feature-engineering 2 scikit-learn 2 lasso-regression 2 ridge-regression 2 ab-testing 2 bagging-ensemble 2 glm 2 insurance 2 model-monitoring 2 mlops-workflow 2 ensemble-learning 1 fungiclef 1 nearest-neighbor-search 1 fortran 1 clustering 1 automatic-differentiation 1 approximate-nearest-neighbor-search 1 out-of-distribution 1 anomaly-detection 1 mlj 1 ml 1 boosting-machine 1 weights-and-biases 1 ipl 1 mlp-regressor 1 pyhton 1 wandb 1 trivago 1 session-based-recommendation-system 1 recommender-system 1 mean-reciprocal-rank 1 lightgbm 1 hotel-recommender 1 data-mining 1 kaggle-dataset 1 grid-search 1 gradient-boosting 1 descision-tree 1 bagging-classifier 1 ada-boost-classifier 1 tree 1 model-trees 1 tfidf-scores 1 text-classification 1 text-analytics 1 python3 1 feature-extraction 1 corpora 1 classification-model 1 pca-analysis 1 matlab 1 lstm-neural-networks 1 data-processing 1 plots-in-python 1 pcr 1 data-imputation 1 correlation-matrix 1 coefficient-of-variation 1 swift-for-tensorflow 1 swift 1 lifeclef 1 knn 1 keepcoding 1 pairwise 1 bing 1 telecommunications 1 cohort-analysis 1 support-vector-machines 1 classification 1