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)
This project hosts the code for implementing the ISAL algorithm for object detection and image classification

Influence Selection for Active Learning (ISAL) This project hosts the code for implementing the ISAL algorithm for object detection and image classifi

25 Sep 11, 2022
Source Code for Simulations in the Publication "Can the brain use waves to solve planning problems?"

Code for Simulations in the Publication Can the brain use waves to solve planning problems? Installing Required Python Packages Please use Python vers

EMD Group 2 Jul 01, 2022
🏎️ Accelerate training and inference of πŸ€— Transformers with easy to use hardware optimization tools

Hugging Face Optimum πŸ€— Optimum is an extension of πŸ€— Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

Hugging Face 842 Dec 30, 2022
Applying curriculum to meta-learning for few shot classification

Curriculum Meta-Learning for Few-shot Classification We propose an adaptation of the curriculum training framework, applicable to state-of-the-art met

Stergiadis Manos 3 Oct 25, 2022
Personalized Federated Learning using Pytorch (pFedMe)

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

Charlie Dinh 226 Dec 30, 2022
robomimic: A Modular Framework for Robot Learning from Demonstration

robomimic [Homepage]   [Documentation]   [Study Paper]   [Study Website]   [ARISE Initiative] Latest Updates [08/09/2021] v0.1.0: Initial code and pap

ARISE Initiative 178 Jan 05, 2023
PyTorch implementation for MINE: Continuous-Depth MPI with Neural Radiance Fields

MINE: Continuous-Depth MPI with Neural Radiance Fields Project Page | Video PyTorch implementation for our ICCV 2021 paper. MINE: Towards Continuous D

Zijian Feng 325 Dec 29, 2022
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

Trieu 6.1k Dec 30, 2022
[ICCV'21] Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

CKDN The official implementation of the ICCV2021 paper "Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment" O

Multimedia Research 50 Dec 13, 2022
Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set

Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje

Robert Krug 3 Feb 06, 2022
ΠšΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Π°Ρ Ρ€Π°Π±ΠΎΡ‚Π° ΠΏΠΎ матСматичСским ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌ машинного обучСния

ML-MathMethods-Test ΠšΠΎΠ½Ρ‚Ρ€ΠΎΠ»ΡŒΠ½Π°Ρ Ρ€Π°Π±ΠΎΡ‚Π° ΠΏΠΎ матСматичСским ΠΌΠ΅Ρ‚ΠΎΠ΄Π°ΠΌ машинного обучСния. ВычислСниС основных статистик, Π΄ΠΈΠ°Π³Ρ€Π°ΠΌΠΌ ΠΈ Π³Ρ€Π°Ρ„ΠΈΠΊΠΎΠ², ΠΏΡ€ΠΎΠ²Π΅Ρ€ΠΊΠ° Ρ€Π°Π·Π»

Stas Ivanovskii 1 Jan 06, 2022
Official PyTorch implementation of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image", ICCV 2019

PoseNet of "Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image" Introduction This repo is official Py

Gyeongsik Moon 677 Dec 25, 2022
A benchmark dataset for mesh multi-label-classification based on cube engravings introduced in MeshCNN

Double Cube Engravings This script creates a dataset for multi-label mesh clasification, with an intentionally difficult setup for point cloud classif

Yotam Erel 1 Nov 30, 2021
Implementation of the "Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos" paper.

Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos Introduction Point cloud videos exhibit irregularities and lack of or

Hehe Fan 101 Dec 29, 2022
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.

2021: A Year Full of Amazing AI papers- A Review πŸ“Œ A curated list of the latest breakthroughs in AI by release date with a clear video explanation, l

Louis-FranΓ§ois Bouchard 2.9k Dec 31, 2022
Provably Rare Gem Miner.

Provably Rare Gem Miner just another random project by yoyoismee.eth useful link main site market contract useful thing you should know read contract

34 Nov 22, 2022
This code is an unofficial implementation of HiFiSinger.

HiFiSinger This code is an unofficial implementation of HiFiSinger. The algorithm is based on the following papers: Chen, J., Tan, X., Luan, J., Qin,

Heejo You 87 Dec 23, 2022
Unofficial PyTorch implementation of TokenLearner by Google AI

tokenlearner-pytorch Unofficial PyTorch implementation of TokenLearner by Ryoo et al. from Google AI (abs, pdf) Installation You can install TokenLear

Rishabh Anand 46 Dec 20, 2022
Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision. ICCV 2021.

Towers of Babel: Combining Images, Language, and 3D Geometry for Learning Multimodal Vision Download links and PyTorch implementation of "Towers of Ba

Blakey Wu 40 Dec 14, 2022
null

DeformingThings4D dataset Video | Paper DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of human

208 Jan 03, 2023