An Approach to Explore Logistic Regression Models

Related tags

Deep Learningucreg
Overview

User-centered Regression

An Approach to Explore Logistic Regression Models

This tool applies the potential of Attribute-RadViz in identifying correlations levels of attributes to explore LR models. We focus on reducing the limitations of using those models in multidimensional data contexts.

The tool includes the following aspects:

  • feature selection,
  • regression model construction,
  • evaluation of binary and multinomial regression, and
  • construction of a panorama for queries over the model.

Authors:

  • Erasmo Artur (USP)
  • Rosane Minghim (UCC)

Installing and running

  • Download this project and unzip in a local directory
  • Open the HTML file in a browser (tested in Chrome, Firefox, and Edge)

Getting started

  • Rendering the first view:
    • Go to Left panel->CSV File->Choose file to pick a CSV file.
    • Then choose a target attribute from Left panel->Target Attribute.
  • Generation of logistic regression models:
    • Select attributes clicking over them and click over the dimensional anchor of the desired label.

The interface

Screen of the interface

  • (a) File opener
  • (b) Target attribute selection
  • (c) Adjust the size of the elements
  • (d) Adjust the opacity of the elements
  • (e) Adjust the strength of RadViz links
  • (f) Adjust the repelling force of the elements (to avoid overlapping)
  • (g) Enable/disable visual widgets of the tool (can increase performance)
    • Information bars: Hide/Show all informations bars
    • Borders of nodes: Hide/Show the borders of the mapped elements
    • Links lines: Hide/Show between DAs and mapped elements
    • Word cloud: Hide/Show a word cloud when hovering DAs
    • Correlation between attributes: Dynamically changes sizes of elements according to the correlation to the hovered one.
  • (h) Choose the evaluation mode in the second view
  • (i) Plot some attribute of the data set directly to the ROC
  • (j) Choose the discretization of the ROC curve
  • (k) Choose the confindence of the LR model
  • (l) Choose the attribute used in to identify mapped items by the tooltip
  • (m) Define the sample size for the view
  • (n) Define the opacity of the elements
  • (o) Adjust the repelling force of the elements (to avoid overlapping)
Single-Stage 6D Object Pose Estimation, CVPR 2020

Overview This repository contains the code for the paper Single-Stage 6D Object Pose Estimation. Yinlin Hu, Pascal Fua, Wei Wang and Mathieu Salzmann.

CVLAB @ EPFL 89 Dec 26, 2022
GLM (General Language Model)

GLM GLM is a General Language Model pretrained with an autoregressive blank-filling objective and can be finetuned on various natural language underst

THUDM 421 Jan 04, 2023
Code for AutoNL on ImageNet (CVPR2020)

Neural Architecture Search for Lightweight Non-Local Networks This repository contains the code for CVPR 2020 paper Neural Architecture Search for Lig

Yingwei Li 104 Aug 31, 2022
GMFlow: Learning Optical Flow via Global Matching

GMFlow GMFlow: Learning Optical Flow via Global Matching Authors: Haofei Xu, Jing Zhang, Jianfei Cai, Hamid Rezatofighi, Dacheng Tao We streamline the

Haofei Xu 298 Jan 04, 2023
Geometric Vector Perceptrons --- a rotation-equivariant GNN for learning from biomolecular structure

Geometric Vector Perceptron Implementation of equivariant GVP-GNNs as described in Learning from Protein Structure with Geometric Vector Perceptrons b

Dror Lab 142 Dec 29, 2022
catch-22: CAnonical Time-series CHaracteristics

catch22 - CAnonical Time-series CHaracteristics About catch22 is a collection of 22 time-series features coded in C that can be run from Python, R, Ma

Carl H Lubba 229 Oct 21, 2022
The challenge for Quantum Coalition Hackathon 2021

Qchack 2021 Google Challenge This is a challenge for the brave 2021 qchack.io participants. Instructions Hello, intrepid qchacker, welcome to the G|o

quantumlib 18 May 04, 2022
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

GCNet for Object Detection By Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu. This repo is a official implementation of "GCNet: Non-local Networ

Jerry Jiarui XU 1.1k Dec 29, 2022
This repo includes our code for evaluating and improving transferability in domain generalization (NeurIPS 2021)

Transferability for domain generalization This repo is for evaluating and improving transferability in domain generalization (NeurIPS 2021), based on

gordon 9 Nov 29, 2022
Codes for AAAI22 paper "Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum"

Paper For more details, please see our paper Learning to Solve Travelling Salesman Problem with Hardness-Adaptive Curriculum which has been accepted a

14 Sep 30, 2022
Implementation of Change-Based Exploration Transfer (C-BET)

Implementation of Change-Based Exploration Transfer (C-BET), as presented in Interesting Object, Curious Agent: Learning Task-Agnostic Exploration.

Simone Parisi 29 Dec 04, 2022
PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

Youngjoon Lee 48 Dec 29, 2022
This project is the PyTorch implementation of our CVPR 2022 paper:

Requirements and Dependency Install PyTorch with CUDA (for GPU). (Experiments are validated on python 3.8.11 and pytorch 1.7.0) (For visualization if

Lei Huang 23 Nov 29, 2022
Learning trajectory representations using self-supervision and programmatic supervision.

Trajectory Embedding for Behavior Analysis (TREBA) Implementation from the paper: Jennifer J. Sun, Ann Kennedy, Eric Zhan, David J. Anderson, Yisong Y

58 Jan 06, 2023
Unpaired Caricature Generation with Multiple Exaggerations

CariMe-pytorch The official pytorch implementation of the paper "CariMe: Unpaired Caricature Generation with Multiple Exaggerations" CariMe: Unpaired

Gu Zheng 37 Dec 30, 2022
A repository with exploration into using transformers to predict DNA ↔ transcription factor binding

Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ↔ transc

Phil Wang 62 Dec 20, 2022
Get started learning C# with C# notebooks powered by .NET Interactive and VS Code.

.NET Interactive Notebooks for C# Welcome to the home of .NET interactive notebooks for C#! How to Install Download the .NET Coding Pack for VS Code f

.NET Platform 425 Dec 25, 2022
Official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks"

Easy-To-Hard The official repository for the paper "Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks". Gett

Avi Schwarzschild 52 Sep 08, 2022
3rd Place Solution of the Traffic4Cast Core Challenge @ NeurIPS 2021

3rd Place Solution of Traffic4Cast 2021 Core Challenge This is the code for our solution to the NeurIPS 2021 Traffic4Cast Core Challenge. Paper Our so

7 Jul 25, 2022
Re-implementation of 'Grokking: Generalization beyond overfitting on small algorithmic datasets'

Re-implementation of the paper 'Grokking: Generalization beyond overfitting on small algorithmic datasets' Paper Original paper can be found here Data

Tom Lieberum 38 Aug 09, 2022