Hitters Linear Regression - Hitters Linear Regression With Python

Related tags

Deep LearningHitters_Linear_Regression
Overview

Hitters_Linear_Regression

image

Kullanacağımız veri seti Carnegie Mellon Üniversitesi'nde bulunan StatLib kütüphanesinden alınmıştır. Veri seti 1988 ASA Grafik Bölümü Poster Oturumu'nda kullanılan verilerin bir parçasıdır. Maaş verileri orijinal olarak Sports Illustrated, 20 Nisan 1987'den alınmıştır. 1986 ve kariyer istatistikleri, Collier Books, Macmillan Publishing Company, New York tarafından yayınlanan 1987 Beyzbol Ansiklopedisi Güncellemesinden elde edilmiştir. Salary yani maaş değişkeninini bu projede linear regression ile tahmin edeceğiz.

Veri setini daha yakından tanımak adına değişkenleri tanıyalım:

AtBat: 1986–1987 sezonunda bir beyzbol sopası ile topa yapılan vuruş sayısı 

Hits: 1986–1987 sezonundaki isabet sayısı 

HmRun: 1986–1987 sezonundaki en değerli vuruş sayısı 

Runs: 1986–1987 sezonunda takımına kazandırdığı sayı 

RBI: Bir vurucunun vuruş yaptığında koşu yaptırdığı oyuncu sayısı 

Walks: Karşı oyuncuya yaptırılan hata sayısı 

Years: Oyuncunun major liginde oynama süresi (sene) 

CAtBat: Oyuncunun kariyeri boyunca topa vurma sayısı 

CHits: Oyuncunun kariyeri boyunca yaptığı isabetli vuruş sayısı 

CHmRun: Oyucunun kariyeri boyunca yaptığı en değerli vuruş sayısı 

CRuns: Oyuncunun kariyeri boyunca takımına kazandırdığı sayı 

CRBI: Oyuncunun kariyeri boyunca koşu yaptırdırdığı oyuncu sayısı 

CWalks: Oyuncun kariyeri boyunca karşı oyuncuya yaptırdığı hata sayısı 

League: Oyuncunun sezon sonuna kadar oynadığı ligi gösteren A ve N seviyelerine sahip bir faktör 

Division: 1986 sonunda oyuncunun oynadığı pozisyonu gösteren E ve W seviyelerine sahip bir faktör 

PutOuts: Oyun icinde takım arkadaşınla yardımlaşma 

Assits: 1986–1987 sezonunda oyuncunun yaptığı asist sayısı 

Errors: 1986–1987 sezonundaki oyuncunun hata sayısı 

Salary: Oyuncunun 1986–1987 sezonunda aldığı maaş(bin uzerinden) 

NewLeague: 1987 sezonunun başında oyuncunun ligini gösteren A ve N seviyelerine sahip bir faktör

Owner
AyseBuyukcelik
AyseBuyukcelik
GitHub Repository
This is the official PyTorch implementation of the CVPR 2020 paper "TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting".

TransMoMo: Invariance-Driven Unsupervised Video Motion Retargeting Project Page | YouTube | Paper This is the official PyTorch implementation of the C

Zhuoqian Yang 330 Dec 11, 2022
Code and data accompanying our SVRHM'21 paper.

Code and data accompanying our SVRHM'21 paper. Requires tensorflow 1.13, python 3.7, scikit-learn, and pytorch 1.6.0 to be installed. Python scripts i

5 Nov 17, 2021
simple demo codes for Learning to Teach with Dynamic Loss Functions

Learning to Teach with Dynamic Loss Functions This repo contains the simple demo for the NeurIPS-18 paper: Learning to Teach with Dynamic Loss Functio

Lijun Wu 15 Dec 30, 2021
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

Jeya Maria Jose 615 Dec 25, 2022
Model-based Reinforcement Learning Improves Autonomous Racing Performance

Racing Dreamer: Model-based versus Model-free Deep Reinforcement Learning for Autonomous Racing Cars In this work, we propose to learn a racing contro

Cyber Physical Systems - TU Wien 38 Dec 06, 2022
An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

An official PyTorch Implementation of Boundary-aware Self-supervised Learning for Video Scene Segmentation (BaSSL)

Kakao Brain 72 Dec 28, 2022
Official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right"

Surface Form Competition This is the official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right" We p

Peter West 46 Dec 23, 2022
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks

SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr

Image Processing Group - BarcelonaTECH - UPC 347 Nov 22, 2022
MMGeneration is a powerful toolkit for generative models, based on PyTorch and MMCV.

Documentation: https://mmgeneration.readthedocs.io/ Introduction English | 简体中文 MMGeneration is a powerful toolkit for generative models, especially f

OpenMMLab 1.3k Dec 29, 2022
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.

collie Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie do

ShopRunner 96 Dec 29, 2022
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

蒋子航 383 Dec 27, 2022
HyperaPy: An automatic hyperparameter optimization framework ⚡🚀

hyperpy HyperPy: An automatic hyperparameter optimization framework Description HyperPy: Library for automatic hyperparameter optimization. Build on t

Sergio Mora 7 Sep 06, 2022
PointCloud Annotation Tools, support to label object bound box, ground, lane and kerb

PointCloud Annotation Tools, support to label object bound box, ground, lane and kerb

halo 368 Dec 06, 2022
data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer"

C2F-FWN data/code repository of "C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer" (https://arxiv.org/abs/

EKILI 46 Dec 14, 2022
Dense Prediction Transformers

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

Intel ISL (Intel Intelligent Systems Lab) 1.3k Dec 28, 2022
【ACMMM 2021】DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning

DSANet: Dynamic Segment Aggregation Network for Video-Level Representation Learning (ACMMM 2021) Overview We release the code of the DSANet (Dynamic S

Wenhao Wu 46 Dec 27, 2022
Person Re-identification

Person Re-identification Final project of Computer Vision Table of content Person Re-identification Table of content Students: Proposed method Dataset

Nguyễn Hoàng Quân 4 Jun 17, 2021
QTool: A Low-bit Quantization Toolbox for Deep Neural Networks in Computer Vision

This project provides abundant choices of quantization strategies (such as the quantization algorithms, training schedules and empirical tricks) for quantizing the deep neural networks into low-bit c

Monash Green AI Lab 51 Dec 10, 2022
Rotary Transformer

[中文|English] Rotary Transformer Rotary Transformer is an MLM pre-trained language model with rotary position embedding (RoPE). The RoPE is a relative

325 Jan 03, 2023
Rede Neural Convolucional feita durante o processo seletivo do Laboratório de Inteligência Artificial da FACOM (UFMS)

Primeira_Rede_Neural_Convolucional Rede Neural Convolucional feita durante o processo seletivo do Laboratório de Inteligência Artificial da FACOM (UFM

Roney_Felipe 1 Jan 13, 2022