Linear regression
How to measure the accuracy of linear regression models
Linear Regression disease disease disease disease disease disease disease disease normal normal normal normal normal normal normal normal normal normal normal normal normal normal normal normal X y i = x T i � + ✏ i = � j X i,j + ✏ i j Fitting error: ✏ i
Linear Regression disease disease disease disease disease disease disease disease normal normal normal normal normal normal normal normal normal normal normal normal normal normal normal normal Assumption: errors are Gaussian noises y = X � + ✏ β ∗ = arg min X X β j X i,j ) 2 ( y i − β i j
Linear Regression β ∗ = arg min X X β j X i,j ) 2 ( y i − β i j β ( y − X β ) T ( y − X β ) = arg min = ( X T X ) − 1 X T y Question: How to derive the closed-form solution?
Clustering
Finding hidden structure in data
Expression analysis Blood Brain Liver
Single-cell expression analysis
Clustering: examples
Network clustering
Clustering
Clustering
Clustering algorithms
K-means
K-means for segmentation
When will K-means fail?
Hierarchical clustering
Agglomerative clustering
Complete Single
Application to breast cancer expression data
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