[Verse 1]
Data points scattered on the plane tonight
Linear regression draws the best fit line
Minimize the squares, that's our guiding light
Ridge adds L-two to keep the weights in line
Lasso brings L-one to make features sparse
Elastic Net combines them, playing both their parts
[Chorus]
Supervised learning, labels guide the way
Ridge Lasso Elastic, regularization stays
SVM margins, kernels transform space
Trees and forests, boosting sets the pace
From Bayes to k-NN, algorithms we embrace
Supervised learning finds the hidden patterns place
[Verse 2]
Support vectors mark the boundary clear
Maximum margins separate what's near
Kernel trick maps to dimensions high
Soft margins let some points slip by
SMO breaks the problem into pairs
Sequential minimal optimization cares
[Chorus]
Supervised learning, labels guide the way
Ridge Lasso Elastic, regularization stays
SVM margins, kernels transform space
Trees and forests, boosting sets the pace
From Bayes to k-NN, algorithms we embrace
Supervised learning finds the hidden patterns place
[Verse 3]
Decision trees split on features best
Information gain puts nodes to test
Bagging samples, builds a forest strong
Random features keep the trees from going wrong
Bootstrap aggregating reduces the variance
Multiple learners give us better performance
[Bridge]
XGBoost gradient boosting fast and true
Learning rates and subsampling too
LightGBM leaf-wise growing scheme
CatBoost handles categories clean
Monotonic constraints keep logic sound
Hyperparameter tuning makes performance bound
[Verse 4]
Naive Bayes assumes independence pure
Conditional probability makes predictions sure
K nearest neighbors votes from closest friends
Distance metrics show where similarity ends
Discriminant analysis finds the class divide
Linear quadratic boundaries decide
[Chorus]
Supervised learning, labels guide the way
Ridge Lasso Elastic, regularization stays
SVM margins, kernels transform space
Trees and forests, boosting sets the pace
From Bayes to k-NN, algorithms we embrace
Supervised learning finds the hidden patterns place
[Outro]
When the data speaks and labels show
These algorithms help the knowledge grow
From regression lines to boosted trees
Supervised learning holds the keys