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Showing posts with label Machine Learning. Show all posts
Showing posts with label Machine Learning. Show all posts

Python: Independent Component Analysis (ICA) versus PCA

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This post demonstrates the usage of Independent Component Analysis (ICA) in Python, a technique akin to PCA but focused on indepe...

Understanding the LSTM model

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This post gives a brief introduction to the basic structure of LSTM (Long-Short Term Memory) model with an intuitive figures and e...

R code : Creating lagged Xs and y for supervised learning

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This post shows a simple R code to create various lagged time series and concatenate them with the original time series. This ca...

R code : Back Transform from Caret's preProcess()

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This post gives a small R code for the back transformation of the caret's preProcess() function , which is not implemented in...

Installing Python and Tensorflow with Jupyter Notebook Configurations

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For a machine or deep learning modeling, Python is widely used with Tensorflow. This post explains the an installation of Python, ...

lambda.min, lambda.1se and Cross Validation in Lasso : Continuous Response

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This post presents a R code for a k-fold cross validation of Lasso in the case of a gaussian regression (continuous Y) . This work easi...

lambda.min, lambda.1se and Cross Validation in Lasso : Binomial Response

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This post explains more details regarding cross validation of Lasso in the case of a binomial response . We implement a R code for a la...

Exclusive Lasso and Group Lasso using R code

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This post shows how to use the R packages for estimating an exclusive lasso and a group lasso. These lasso variants have a given groupi...
6 comments:

Machine Learning : Workflow

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This post gives a brief introduction to a workflow of machine learning model and mostly used R packages before diving into the details ...

Understanding Gradient Descent Algorithm with Python code

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Gradient Descent (GD) is the basic optimization algorithm for machine learning or deep learning. This post explains the basic conce...
2 comments:

Understanding Logistic Regression

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This post explains the logistic regression and implements R code for the estimation of its parameters.

Sign Constrained Lasso with R code

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This post explains how to implement the sign constrained lasso with ridge, and linear regression model. The restrictions of expected si...

Lasso Regression Model with R code

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Tibshirani (1996) introduces the so called LASSO (Least Absolute Shrinkage and Selection Operator) model for the selection and shrink...