The Google Brain team created TensorFlow, an open-source library. It was designed for activities that need a lot of numerical computations.
TensorFlow was designed specifically for machine learning and deep learning networks. TensorFlow ran faster than python code thanks to the use of C/C++ as a backend.
In this tutorial we are going to discuss DT package from R.
DT stands for data tables and datatable() is the main function of DT package.
datatable() is completely different from data.table() function
DT package is very easy to use and based on this package can filter, search export data into different formats easily.
A lack of fit test is used to determine whether a full regression model fits a dataset significantly better than a reduced version of the model.
Consider the following regression model, which has four predictor variables.
Y = β0 + β1×1 + β2×2 + β3×3 + β4×4 + ε
A nested model is demonstrated by the following model, which contains only two of the original predictor variables.
Y = β0 + β1×1 + β2×2 + ε
We can use a Lack of Fit Test with the following null and alternative hypotheses to see if these two models differ significantly.
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