Reproducibility and Replicability of Web Measurement Studies

Last update: Dec 31, 2022

Overview

Reproducibility and Replicability of Web Measurement Studies

This repository holds additional material to the paper "Reproducibility and Replicability of Web Measurement Studies" submitted to the ACM Web Conference 2022.

The repository is organized as follows:

In 01_Plots, one finds all codes and the underlying data used to produce the plots in the paper
In 02_Data, we provide a link to the raw measurement results.
In 03_Framework, one can find the framework we used for our measurement study.
In 04_Paper_Survey, we provide a listing of all analyzed papers.
Finally, in 05_misc, we provide further data (e.g., the used EasyList, list of visited pages).

Owner

GitHub Repository

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Reproducibility and Replicability of Web Measurement Studies

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Overview

Reproducibility and Replicability of Web Measurement Studies

Owner

PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

A simple machine learning package to cluster keywords in higher-level groups.

Official code for HH-VAEM

Turning images into '9-pan' palettes using KMeans clustering from sklearn.

Simple structured learning framework for python

Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

LinearRegression2 Tvads and CarSales

Neural Machine Translation (NMT) tutorial with OpenNMT-py

Factorization machines in python

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

hgboost - Hyperoptimized Gradient Boosting

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

A Pythonic framework for threat modeling

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using Machine Learning Algorithm to classification AppleStore application

Houseprices - Predict sales prices and practice feature engineering, RFs, and gradient boosting