Giter VIP home page Giter VIP logo

mnar_exp's Introduction

MNAR_exp

  1. Run create_data.ipynb: load raw data, do the normalization, and do the datasplit of each data. datalist : [

    "banknote":https://archive.ics.uci.edu/dataset/267/banknote+authentication 1372 * 5 Classification 1. variance of Wavelet Transformed image (continuous) 2. skewness of Wavelet Transformed image (continuous) 3. curtosis of Wavelet Transformed image (continuous) 4. entropy of image (continuous) 5. class (integer)

    "concrete_compression":https://archive.ics.uci.edu/dataset/165/concrete+compressive+strength Regression Number of instances 1030 Number of Attributes 9 Attribute breakdown 8 quantitative input variables, and 1 quantitative output variable

    "wine_quality_white": https://archive.ics.uci.edu/dataset/186/wine+quality "wine_quality_red": Regression Number of instances 1599 red , 4898 white Number of Attributes 12 Attribute breakdown 11 quantitative input variables, and 1 quantitative output variable

    "california":https://scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_california_housing.html Regression Samples total 20640 feature 9 + 1

    "climate_model_crashes":https://archive.ics.uci.edu/dataset/252/climate+model+simulation+crashes Classification (Discrete Variable Col1, Col2 Mix Type) Column 1: Latin hypercube study ID (study 1 to study 3)

    Column 2: simulation ID (run 1 to run 180)

    Columns 3-20: values of 18 climate model parameters scaled in the interval [0, 1]

    Column 21: simulation outcome (0 = failure, 1 = success)

    "connectionist_bench_sonar":https://archive.ics.uci.edu/dataset/151/connectionist+bench+sonar+mines+vs+rocks Classification Instances 208, Features 60

    "qsar_biodegradation":https://archive.ics.uci.edu/dataset/254/qsar+biodegradation 1055 instances Classification 41 molecular descriptors and 1 experimental class:

    "yeast":https://archive.ics.uci.edu/dataset/110/yeast 1484 * 8+1, Classification

    "yacht_hydrodynamics":https://archive.ics.uci.edu/dataset/243/yacht+hydrodynamics Regression, 308 * 6+1 ]

  2. Runcreate_missing.ipynb Create Missing Masks, include missing rate

    • Add five fold visualization
  3. Run create_visualization.ipynb Create Missing Mech ScatterPlot, Missing Rate Plot, Missing Distribution Plot

  4. Run models Under Model folders, each model will create a train and test data mean.ipynb fast , knn.ipynbfast , missforest.ipynbslow operating time imputation from Sklearn XBG.ipynb Missing Imputer from https://github.com/sjtupig/MissingImputer MICE.ipynb

  5. Run Evaluation RMSE rmse.ipynb Downstream mltask.ipynb if need to normalization? results display results_printour.ipynb and visualization

Todo: pipline finished โœ” 8 more dataset MIWAE, notMIWAE, OT, GAIN, MCFLOW, TabCSDI, Hyper imputer existing model new: MIDAE VAEI GINN VGAIN<- check data type

mnar_exp's People

Contributors

echoid avatar dunghuynhandy avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.