Study Notes of Udacity A/B Testing
Study note of Udacity A/B Testing course. ...
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Spark SQL & DataFrame, SparkETL
Pyspark code of Big Data Essentials: HDFS, MapReduce and Spark RDD ...
Study Note: Assessing Model Accuracy
MSE/Bias-Variance Trade-Off/K-Nearest Neighbors ...
Study Note: Clustering
K-Means Clustering/Hierarchical Clustering Algorithm ...
Study Note: Dimension Reduction - PCA, PCR
Dimension Reduction Methods Subset selection and shrinkage methods all use the original predictors, X1,X2, . . . , Xp. Dimension Reduction Methods transform the predictors and then fit a least squares model using the transformed variables. Approach Let $Z_1,Z_2, . . . ,Z_M$ represent $M < p$ linear combinations of our original $p$ predictors. That is, $$ \begin{align} Z_m=\sum_{j=1}^p\phi_{jm}X_j \end{align} $$ ...