Project Objective: To analyze the impact of PCA on computational efficiency and model reliability using the high-dimensional MNIST dataset. This work demonstrates the power of Principal Component ...
We are using three-dimensional data named Feature_1, Feature_2, and Feature_3. data = pd.read_csv("Sythetic_Correlated_Data.csv") data.head() # plot 3d scatter plot using go library import ...
Normalizing out the 1st and more components from the data. This is usefull if the data is seperated in its first component(s) by unwanted or biased variance. Such as sex or experiment location etc.
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