K-Means Clustering and Hierarchical Clustering Unsupervised Learning Solution in Python3.

Overview

Unsupervised Learning - K-Means Clustering and Hierarchical Clustering - The Heritage Foundation's Economic Freedom Index Analysis 2019 - By David Salako.

Background and Context

Created in 1995 by the Heritage Foundation, The Index of Economic Freedom is a ranking created to measure the economic freedom in the countries of the world.

Now, in its 25th edition, The Economic Freedom Index is poised to help readers track over two decades of the advancement in economic freedom, prosperity, and opportunity and promote these ideas in their homes, schools, and communities.

The Index covers 12 freedoms, from property rights to financial freedom, in 186 countries.

Objective:

As a data scientist, I have been tasked to (1) analyze the data, (2) use clustering algorithms to identify different groups of countries based on economic freedom, and (3) list the insights from the analysis.

Data Dictionary & Description:

The data comprises factors indicating economic freedom. The list of variables in the data is given below. All these features are self-explanatory and more details can be found in the data source listed below.

  • CountryID
  • Country Name
  • WEBNAME
  • Region
  • World Rank
  • Region Rank
  • 2019 Score
  • Property Rights
  • Judical Effectiveness
  • Government Integrity
  • Tax Burden
  • Gov't Spending
  • Fiscal Health
  • Business Freedom
  • Labor Freedom
  • Monetary Freedom
  • Trade Freedom
  • Investment Freedom
  • Financial Freedom
  • Tariff Rate (%)
  • Income Tax Rate (%)
  • Corporate Tax Rate (%)
  • Tax Burden % of GDP
  • Gov't Expenditure % of GDP
  • Country
  • Population (Millions)
  • GDP (Billions, PPP)
  • GDP Growth Rate (%)
  • 5 Year GDP Growth Rate (%)
  • GDP per Capita (PPP)
  • Unemployment (%)
  • Inflation (%)
  • FDI Inflow (Millions)
  • Public Debt (% of GDP)

Data Source:

This dataset belongs to The Heritage Foundation and is freely available to download on their website (https://www.heritage.org/index/ranking).

The Index of Economic Freedom considers every component equally important in achieving the positive benefits of economic freedom.

Each freedom is weighted equally in determining country scores.

Countries considering economic reforms may find significant opportunities for improving economic performance in those factors in which they score the lowest.

These factors may indicate significant binding constraints on economic growth and prosperity.

Owner
David Salako
David Salako
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver

Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape

394 Dec 30, 2022
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa

MIND 478 Jan 01, 2023
This is the official repository of Music Playlist Title Generation: A Machine-Translation Approach.

PlyTitle_Generation This is the official repository of Music Playlist Title Generation: A Machine-Translation Approach. The paper has been accepted by

SeungHeonDoh 6 Jan 03, 2022
PyTorch ,ONNX and TensorRT implementation of YOLOv4

PyTorch ,ONNX and TensorRT implementation of YOLOv4

4.2k Jan 01, 2023
Tensorflow port of a full NetVLAD network

netvlad_tf The main intention of this repo is deployment of a full NetVLAD network, which was originally implemented in Matlab, in Python. We provide

Robotics and Perception Group 225 Nov 08, 2022
Code and data for the EMNLP 2021 paper "Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts". Coming soon!

ToxiChat Code and data for the EMNLP 2021 paper "Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts". Install depen

Ashutosh Baheti 11 Jan 01, 2023
Existing Literature about Machine Unlearning

Machine Unlearning Papers 2021 Brophy and Lowd. Machine Unlearning for Random Forests. In ICML 2021. Bourtoule et al. Machine Unlearning. In IEEE Symp

Jonathan Brophy 213 Jan 08, 2023
Implement object segmentation on images using HOG algorithm proposed in CVPR 2005

HOG Algorithm Implementation Description HOG (Histograms of Oriented Gradients) Algorithm is an algorithm aiming to realize object segmentation (edge

Leo Hsieh 2 Mar 12, 2022
PyArmadillo: an alternative approach to linear algebra in Python

PyArmadillo is a linear algebra library for the Python language, with an emphasis on ease of use.

Terry Zhuo 58 Oct 11, 2022
PoolFormer: MetaFormer is Actually What You Need for Vision

PoolFormer: MetaFormer is Actually What You Need for Vision (arXiv) This is a PyTorch implementation of PoolFormer proposed by our paper "MetaFormer i

Sea AI Lab 1k Dec 30, 2022
The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization

PRIMER The official code for PRIMER: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization. PRIMER is a pre-trained model for mu

AI2 111 Dec 18, 2022
Implementation of Bagging and AdaBoost Algorithm

Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win

Zechen Ma 1 Nov 01, 2021
DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021)

Evaluation, Training, Demo, and Inference of DeFMO DeFMO: Deblurring and Shape Recovery of Fast Moving Objects (CVPR 2021) Denys Rozumnyi, Martin R. O

Denys Rozumnyi 139 Dec 26, 2022
Convnext-tf - Unofficial tensorflow keras implementation of ConvNeXt

ConvNeXt Tensorflow This is unofficial tensorflow keras implementation of ConvNe

29 Oct 06, 2022
Face Synthetics dataset is a collection of diverse synthetic face images with ground truth labels.

The Face Synthetics dataset Face Synthetics dataset is a collection of diverse synthetic face images with ground truth labels. It was introduced in ou

Microsoft 608 Jan 02, 2023
State-Relabeling Adversarial Active Learning

State-Relabeling Adversarial Active Learning Code for SRAAL [2020 CVPR Oral] Requirements torch = 1.6.0 numpy = 1.19.1 tqdm = 4.31.1 AL Results The

10 Jul 14, 2022
Realtime_Multi-Person_Pose_Estimation

Introduction Multi Person PoseEstimation By PyTorch Results Require Pytorch Installation git submodule init && git submodule update Demo Download conv

tensorboy 1.3k Jan 05, 2023
Making self-supervised learning work on molecules by using their 3D geometry to pre-train GNNs. Implemented in DGL and Pytorch Geometric.

3D Infomax improves GNNs for Molecular Property Prediction Video | Paper We pre-train GNNs to understand the geometry of molecules given only their 2D

Hannes Stärk 95 Dec 30, 2022
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
LAVT: Language-Aware Vision Transformer for Referring Image Segmentation

LAVT: Language-Aware Vision Transformer for Referring Image Segmentation Where we are ? 12.27 目前和原论文仍有1%左右得差距,但已经力压很多SOTA了 ckpt__448_epoch_25.pth mIoU

zichengsaber 60 Dec 11, 2022