Logistic Regression (Episode 9) The Effective Data Scientist podcast

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Logistic regression (Episode 9)

לפני שנתיים 16:20

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AAC•בית הפרקים

תוכן מסופק על ידי Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

Logistic regression is a beautiful tool for modeling a binary dependent variable, although many more complex extensions exist. In the show, we will speak about the generalized linear model family, logit and probit functions, interpretations, and practicalities.

Resources:

● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.

● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)

… continue reading

24 פרקים

#Science #Natural Sciences #Alexander Schacht and Paolo Eusebi #Alexander Schacht #Paolo Eusebi #Data Science #Data Scientist

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Logistic regression (Episode 9)

The Effective Data Scientist

published לפני שנתיים

שתפו

AAC•בית הפרקים

תוכן מסופק על ידי Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי Alexander Schacht and Paolo Eusebi, Alexander Schacht, and Paolo Eusebi או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

Logistic regression is a beautiful tool for modeling a binary dependent variable, although many more complex extensions exist. In the show, we will speak about the generalized linear model family, logit and probit functions, interpretations, and practicalities.

Resources:

● McCullagh, Peter, and John A. Nelder. Generalized linear models. Routledge, 1983.

● Faraway, Julian J. Extending the linear model with R: generalized linear, mixed effects and nonparametric regression models. Chapman and Hall/CRC, 2016. (http://https://julianfaraway.github.io/faraway/ELM/)

… continue reading

24 פרקים

#Science #Natural Sciences #Alexander Schacht and Paolo Eusebi #Alexander Schacht #Paolo Eusebi #Data Science #Data Scientist

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