Hitters Linear Regression - Hitters Linear Regression With Python

Related tags

Deep Learning Hitters_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

You might also like...
A python library to build Model Trees with Linear Models at the leaves.
A python library to build Model Trees with Linear Models at the leaves.

A python library to build Model Trees with Linear Models at the leaves.

Marco Cerliani 212 Dec 30, 2022
Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy
Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy

Creating a Linear Program Solver by Implementing the Simplex Method in Python with NumPy Simplex Algorithm is a popular algorithm for linear programmi

Reda BELHAJ 2 Oct 12, 2022
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 4, 2023
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 5.7k Feb 12, 2021
Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible

Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible, to be the most reliable with the least complexity possible

Nikolas B Virionis 2 Aug 1, 2022
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

H2O H2O is an in-memory platform for distributed, scalable machine learning. H2O uses familiar interfaces like R, Python, Scala, Java, JSON and the Fl

H2O.ai 6.1k Jan 5, 2023
An automated algorithm to extract the linear blend skinning (LBS) from a set of example poses
An automated algorithm to extract the linear blend skinning (LBS) from a set of example poses

Dem Bones This repository contains an implementation of Smooth Skinning Decomposition with Rigid Bones, an automated algorithm to extract the Linear B

Electronic Arts 684 Dec 26, 2022
Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks
Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks

PWLQ Updates 2020/07/16 - We are working on getting permission from our institution to release our source code. We will release it once we are granted

null 54 Dec 15, 2022
The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.
The code release of paper 'Domain Generalization for Medical Imaging Classification with Linear-Dependency Regularization' NIPS 2020.

Domain Generalization for Medical Imaging Classification with Linear Dependency Regularization The code release of paper 'Domain Generalization for Me

Yufei Wang 56 Dec 28, 2022
Owner
AyseBuyukcelik
AyseBuyukcelik
GitHub
Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D Diffusion Equation using Standard Wall Function, 2D Heat Conduction Convection equation with Dirichlet & Neumann BC, full Navier-Stokes Equation coupled with Poisson equation for Cavity and Channel flow in 2D using Finite Difference Method & Finite Volume Method.

Navier-Stokes-numerical-solution-using-Python- Python script for Linear, Non-Linear Convection, Burger’s & Poisson Equation in 1D & 2D, 1D D

null 89 Jan 4, 2023
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the moment, only TensorFlow sequential models are supported. Interfaces to either the Pyomo or Gurobi modeling environments are offered.

ChemEngAI 40 Dec 27, 2022
Simple Linear 2nd ODE Solver GUI - A 2nd constant coefficient linear ODE solver with simple GUI using euler's method

Simple_Linear_2nd_ODE_Solver_GUI Description It is a 2nd constant coefficient li

:) 4 Feb 5, 2022
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose

Erik Linder-Norén 21.8k Jan 9, 2023
Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.

Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p

DIKSHA DESWAL 1 Dec 29, 2021
The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

null 1 Jan 27, 2022
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

Arsenii Senya Ashukha 80 Sep 17, 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
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

Chao Ma 3k Jan 3, 2023
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

Chao Ma 2.8k Feb 12, 2021