Linked Questions

123
votes
3answers
261k views

What is the difference between linear regression and logistic regression?

What is the difference between linear regression and logistic regression? When would you use each?
17
votes
3answers
31k views

How to decide which glm family to use?

I have fish density data that I am trying to compare between several different collection techniques, the data has lots of zeros, and the histogram looks vaugley appropriate for a poisson distribution ...
10
votes
3answers
4k views

What regression model is the most appropriate to use with count data?

I am trying to get a little into statistics, but I am stuck with something. My data are as follows: ...
25
votes
2answers
7k views

Intuition behind logistic regression

Recently I began studying machine learning, however I failed to grasp the intuition behind logistic regression. The following are the facts about logistic regression that I understand. As the basis ...
2
votes
2answers
3k views

Understand Link Function in Generalized Linear Model

I am still trying to learn (may be the terminology issue) what does "link function" mean. For example, in logistic regression, we assume response variable is coming form binomial distribution. The <...
2
votes
3answers
2k views

Does Categorical Variable need normalization/standardization?

since we do normalize as 10kg >>> 10 grams or 1000 >> 10. so incase of one hot encoding eg male=0 and female =1, are we giving more weight to female as 1>0 for training our models?
3
votes
2answers
489 views

Do we always assume cross entropy cost function for logistic regression solution unless stated otherwise?

I am using Matlab glmfit for logistic regression. Now I know that usually people use the cross entropy to evaluate the error in predictions against the true labels ( which different than the linear ...
0
votes
1answer
393 views

One-hot-encoding gives untractable amount of classes

I'm performing regression on the price of bycicles based on their brand, model and submodel. These features are hierarchical: one model belongs only to one brand but one brand can have many models. ...
2
votes
2answers
274 views

In neural network, what is the good way to represent ordinal/ratio data such as age, hour, day of week?

I know that age is often represented as a numerical feature. For example in linear regression, it is common to use one single independent variable (IV) to represent it. However, one single IV cannot ...
2
votes
1answer
214 views

Generalized linear model - confused by definition [duplicate]

I'm beginning with the regression analysis and I'm quite confused with the generalized linear regression. I understand, that the ordinary linear models can be described with a formula $$ y_i = \...
3
votes
1answer
99 views

Is it valid to have all zeroes in a One-Hot Encoded categorical feature?

I'm building an MLP classification model and one of my features is the name of certain products. These names can be anything and in theory there could be an infinite number of different names in the ...