In statistieken wordt het logistieke model (of logit-model) gebruikt om de waarschijnlijkheid van een bepaalde klasse of bestaande gebeurtenis te modelleren, zoals slagen / mislukken, winnen / verliezen, levend / dood of gezond / ziek. Dit kan worden uitgebreid om verschillende soorten gebeurtenissen te modelleren, zoals bepalen of een afbeelding een kat, hond, leeuw, enz. Bevat. Elk object dat in de afbeelding wordt gedetecteerd, krijgt een waarschijnlijkheid tussen 0 en 1 toegewezen, met een som van één.
Logistische regressie is een statistisch model dat in zijn basisvorm een logistieke functie gebruikt om een binair afhankelijke variabele te modelleren, hoewel er veel complexere uitbreidingen bestaan. Bij regressieanalyse is logistische regressie [1] (of logitregressie) het schatten van de parameters van een logistiek model (een vorm van binaire regressie). Wiskundig gezien heeft een binair logistiek model een afhankelijke variabele met twee mogelijke waarden, zoals geslaagd / mislukt, die wordt weergegeven door een indicatorvariabele, waarbij de twee waarden worden aangeduid met "0" en "1". In het logistieke model is de log-odds (de logaritme van de odds) voor de waarde met het label "1" een lineaire combinatie van een of meer onafhankelijke variabelen ("voorspellers"); de onafhankelijke variabelen kunnen elk een binaire variabele zijn (twee klassen, gecodeerd door een indicatorvariabele) of een continue variabele (elke reële waarde). De overeenkomstige waarschijnlijkheid van de waarde met het label "1" kan variëren tussen 0 (zeker de waarde "0") en 1 (zeker de waarde "1"), vandaar de labeling; de functie die log-odds omzet in waarschijnlijkheid is de logistieke functie, vandaar de naam.
Overzicht cursussen Logistische regressie
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What is this course all about? This course is all about credit scoring / logistic regression model building using SAS. It explains There course promises to explain concepts in a crystal clear manner. It goes through the practical issue faced by analyst. Some of the discussion item would be How to clarify object..
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This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis placed on the interpretation of the results. It covers the skills required to assemble analysis flow diagrams using the rich tool set and predictive modeling. Ready-to-use procedures handle a wide range o..
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This course is a lead-in to deep learning and neural networks - it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might..
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You're looking for a complete Classification modeling course that teaches you everything you need to create a Classification model in Python, right?You've found the right Classification modeling course!After completing this course you will be able to:Identify the business problem which can be solved using Classificatio..
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You're looking for a complete Classification modeling course that teaches you everything you need to create a Classification model in R, right?You've found the right Classification modeling course covering logistic regression, LDA and kNN in R studio!After completing this course, you will be able to:· Identify the bus..
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You're looking for a complete Linear Regression and Logistic Regression course that teaches you everything you need to create a Linear or Logistic Regression model in Python, right?You've found the right Linear Regression course!After completing this course you will be able to:Identify the business problem which can be..
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This course is a workshop on logistic regression using R. The course Doesn't have much of theory - it is more of execution of R command for the purposeProvides step by step process detailsStep by step executionData files for the modelingExcel file containing output of these steps The content of the course is as follows..
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Included in this course is an e-book and a set of slides. The course is divided into two parts. In the first part, students are introduced to the theory behind logistic regression. The theory is explained in an intuitive way. The math is kept to a minimum. The course starts with an introduction to contingency tables, i..
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In the this course, i have shared complete process (A to Z ) based on my published articles, about how to evaluate and compare the results of applying the multivariate logistic regression method in Hazard prediction mapping using GIS and R environment.Since last decade, geographic information s..
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Why Logistic Regression? If you would like to become a data analyst/data scientist or take up a project on data analytics, then knowledge on predictive analytics is a key milestone as a large fraction of data analytics projects will be on predictive analytics. Logistic Regression is one of the most commonly used predi..
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In this course, I will teach you one of the most commonly used classification techniques in data science, machine learning and statistics and that is: Binary Logistic Regression.A binomial logistic regression is used to predict the binary output (yes/no, true/false, sick/healthy) based on one or more continuous indepen..
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In statistics, Logistic Regression, or logit regression, or logit model is a regression model where the dependent variable (DV) is categorical. This article covers the case of a binary dependent variable—that is, where the output can take only two values, "0" and "1", which represent outcomes such as pass/fail, win/l..
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This is a hands-on training class for those of you who want to learn or improve predictive modeling skills. We will focus on developing and validating a logistic regression model in this class. We will walk you through our 6-step modeling process step-by-step. Together, we will solve a real-world modeling project wi..
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An easy introduction to Logit and Probit regression.Learning and applying new statistical techniques can often be a daunting experience."Easy Statistics" is designed to provide you with a compact, and easy to understand, course that focuses on the basic principles of statistical methodology.This course will focus on th..
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Social research with Logistic Regression in SPSS: A Complete Guide for the Social SciencesThe only course on Udemy that shows you how to perform, interpret and visualize logistic regression in SPSS, using a real world example, using the quantitative research process. Follow along with me as I talk you through everythin..
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Did you know that approximately 70% of data science problems involve classification and logistic regression is a common solution for binary problems?Logistic regression has many applications in data science, but in the world of healthcare, it can really drive life-changing action.In this SuperDataScience case study cou..
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