menghonghan

chatgpt-on-wechat

COVID-19-Tracker

GUI designed by Plotly Dash

Grocery-Shopping-Behavior-Big-Data-Analysis

Processed over 30 million observations; conducted inactive customer diagnosis and loyalism analysis using MySQL; visualized consumer behavior on private labeled product with Python (matplot, seaborn)

Healthcare-Data-Mining-Projects

Data mining projects include predicting risk score of chronic diseases with NHANES data and analysis of patient and insurance claim data.

k-Means-Clustering

K-Means clustering revision with silhouette score

Massive-Data-Mining

Codes for COSI-120A Massive Data Mining

MetaCost

P. Domingos proposed a principled method for making an arbitrary classifier cost-sensitive by wrapping a cost-minimizing procedure around it. The procedure, called MetaCost, treats the underlying classifier as a black box, requiring no knowledge of its functioning or change to it.

Predict-small-hydro-production-in-California

Using regression (multi-linear regression), classification (KNN, Random Forest, Logistic regression, LGBTree), clustering (k-means) models to predict the production of small hydro and try to find out main impactors and certain patterns using R.

Tansfer-Feature-Learing-with-JDA-implementation-

The introduction and code implementation of the paper "Transfer Feature Learning with Joint Distribution Adaptation"

Urban-Sound-Classification

Using UrbanSound8K dataset from Kaggle, conducted feature extraction by MFCC, MEL-Spectrogram and Chroma_stft, trained a 2D CNN, achieved accuracy of 92.8 %, using Python (tensorflow, kera, librosa)

menghonghan/Tansfer-Feature-Learing-with-JDA-implementation-

The introduction and code implementation of the paper "Transfer Feature Learning with Joint Distribution Adaptation"

menghonghan/Healthcare-Data-Mining-Projects

Data mining projects include predicting risk score of chronic diseases with NHANES data and analysis of patient and insurance claim data.

menghonghan/Urban-Sound-Classification

Using UrbanSound8K dataset from Kaggle, conducted feature extraction by MFCC, MEL-Spectrogram and Chroma_stft, trained a 2D CNN, achieved accuracy of 92.8 %, using Python (tensorflow, kera, librosa)

menghonghan/chatgpt-on-wechat

menghonghan/COVID-19-Tracker

GUI designed by Plotly Dash

menghonghan/Grocery-Shopping-Behavior-Big-Data-Analysis

Processed over 30 million observations; conducted inactive customer diagnosis and loyalism analysis using MySQL; visualized consumer behavior on private labeled product with Python (matplot, seaborn)

menghonghan/k-Means-Clustering

K-Means clustering revision with silhouette score

menghonghan/Massive-Data-Mining

Codes for COSI-120A Massive Data Mining

menghonghan/MetaCost

P. Domingos proposed a principled method for making an arbitrary classifier cost-sensitive by wrapping a cost-minimizing procedure around it. The procedure, called MetaCost, treats the underlying classifier as a black box, requiring no knowledge of its functioning or change to it.

menghonghan/Predict-small-hydro-production-in-California

Using regression (multi-linear regression), classification (KNN, Random Forest, Logistic regression, LGBTree), clustering (k-means) models to predict the production of small hydro and try to find out main impactors and certain patterns using R.

menghonghan/Pypeteer-QiChacha

Using Pypeteer crawled basic information and Administrative penalty information

menghonghan/sturmgang

menghonghan/transferlearning

Everything about Transfer Learning and Domain Adaptation--迁移学习