ML classifications I have a doubt in below ML families.
If we are predicting: Yes,  then we have classification and regression
If No, then we have clustering 
In clustering, we have K-means algo
In classification we predict discrete values, so we have logistic regression, KNN, and NN
In Regression we predict continuous values, so we have Simple Linear and Multiple Linear regression, also called as causal models
Then we have TimeSeries, with Single, Double and Triple exponential models. And ARIMA, SARIMA models
ARIMA combines Regression and Simple means(Moving Average). Now my question is, does TimeSeries come under classification or Regression? 
 A: Strictly speaking, time series methods don't correspond to a specific family of ML models like classification or regression etc... 
They are more of a domain of application, similar to natural language processing, image processing, etc... 
Models from the Exponential Smoothing family are similar in spirit to regression models, however they are different from regression top problems in the sense that they are sequential and take a variable (possibly infinite number of inputs). You can see this by expanding the expression of an exponential smoothing model.
ARIMA models are an interesting case: If they have only an AR component (meaning ARIMA(p,d,q) with q=0) then they are regression models (AR stands for Auto-Regression after all) - however if the have an MA component, then they fall in the same category as Exponential Smoothing models. 
See this post for what ES are not considered regression models and this post for why the MA component of ARIMA models makes them different from regression models.    
