Makes Interactive Chart Widget, Cleans raw data, Runs baseline models, Interactive hyperparameter tuning & tracking
common used Recommend Baseline Model, including the traditional statistical model, and the Nerual Network Model. Focus on the SRS (Sequential Recommend System).
2019语言与智能技术竞赛，信息抽取任务的基线模型python3代码。模型包括：关系抽取（多标签模型）和实体抽取（序列标注模型）
Movie Recommendation System
Automatically generate a pdf report containing feature importance, baseline modelling, spurious correlation detection, and more, from a single command line input for any given ML CSV file
A retail analytics capstone that converts transactions into a calendar intelligence system. It quantifies day-of-week and monthly seasonality, builds a baseline expected revenue model, detects event-like spike days using robust residual z-scores, and explains spikes via transactions, units, AOV, and category mix, with a Streamlit dashboard+exports.
Fake news headlines in the Tamil regional language.
This is a Time Series Forecasting and Regression solution to project the no. of pick-ups at and around a given region at a given time in the city of New York, USA.
Baseline models for HIPE-2022
The baseline code for the CLPsych 2021 Shared Task.
Implemented Linear Regression using scikit-learn to predict housing prices. Evaluated model performance using R² score (~0.64) and residual distribution analysis to assess prediction errors and regression assumptions.
Baseline identification for Energy Performance Contracts
All asignment from data science bootcamp by Dibimbing.id
This repo presents a detailed performance analysis of AdaptiveBayes as a replacement for LogisticRegression as a baseline model. Results are based on classic ML datasets and a wide range of large-scale benchmarks.
architecture performance on CIFAR10 without tricks
ML-models, Prediction, Onset of Diabetes, PIMA Indian Dataset, Baseline-model
Baseline ML models for AI-generated text detection (TF-IDF + Logistic Regression, evaluation metrics).
Implementation for the Classification and Evaluation models as part of the Introduction to Machine Learning (COMP90049) course at The University of Melbourne.
Multinomial logistic regression modeling used to determine influential factors in nicotine usage status
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