How to measure the agreement between two raters? - Cohen's Kappa Coefficient

 The kappa coefficient is a statistic that measures the agreement between raters. It is commonly used in mental health and psychosocial studies. The kappa coefficient can be used for scales with more than two categories, and its range of possible values is from −1 to 1.

Cohen’s kappa is a quantitative measure of reliability for two raters that are rating the same thing, correcting for how often the raters may agree by chance.

In other words, a model will have high kappa score if there is a big differefence between the accuracy and null rate error.

kappa = (Observed agreement - Expected Agreement) / ( 1 - Expected agreement )

Logistic Regression

 Definition:

Logistic Regression is a Supervised learning algorithm that makes use of logistic functions to predict the probability of a Binary outcome.

- outcome limited to two possible outcomes: yes/no, 0/1, or true/false.

Logistic regression analyzes the relationship between one or more independent variables and classifies data into discrete classes. It is extensively used in predictive modeling, where the model estimates the mathematical probability of whether an instance belongs to a specific category or not.

Logistic regression uses a logistic function called a sigmoid function to map predictions and their probabilities. The sigmoid function refers to an S-shaped curve that converts any real value to a range between 0 and 1.

Types of Logistic Regression:

1. Binary Logistic Regression:
   The dependent variable has only two 2 possible outcomes/classes.
   Example-Male or Female.
2. Multinomial Logistic Regression:
   The dependent variable has only two 3 or more possible outcomes/classes without ordering.
   Example: Predicting food quality.(Good,Great and Bad).
3. Ordinal Logistic Regression:
   The dependent variable has only two 3 or more possible outcomes/classes with ordering. Example: Star rating from 1 to 5

Reference:

Wikipedia

Origin of LR