ml
Machine learning: regression, classification, clustering, preprocessing.
Load with: use ml
Quick example
use ml
result = mllbl("value", "value")
prn(result)Functions
Dataset
mlne()
Creates a new instance.
mllbl(d, cols)
Performs the operation. Takes d, cols.
mladd(d, row)
Performs the operation. Takes d, row.
mlcol(d, c)
Performs the operation. Takes d, c.
mlnrm(d, c, mth)
Removes an item. Takes d, c, mth.
Train/test split
mlspl(d, ratio)
Performs the operation. Takes d, ratio.
Linear Regression
mlnlr()
Performs the operation.
mlft1(m, x, y)
Performs the operation. Takes m, x, y.
mlpr4(m, x)
Performs the operation. Takes m, x.
mlscr(m, x, y)
Creates a new instance. Takes m, x, y.
Logistic Regression
mlnlg()
Performs the operation.
mlftl(m, x, y, opts)
Performs the operation. Takes m, x, y, opts.
mlsgm(z)
Performs the operation. Takes z.
mlpr1(m, x)
Performs the operation. Takes m, x.
Decision Tree
mlndt(maxd, mins)
Performs the operation. Takes maxd, mins.
mlftd(m, x, y)
Performs the operation. Takes m, x, y.
mlpr2(m, x)
Performs the operation. Takes m, x.
Random Forest
mlnrf(nt, maxd)
Performs the operation. Takes nt, maxd.
mlftr(m, x, y)
Performs the operation. Takes m, x, y.
mlpr6(m, x)
Performs the operation. Takes m, x.
K-Means Clustering
mlnkm(k)
Performs the operation. Takes k.
mlft0(m, x, iters)
Performs the operation. Takes m, x, iters.
mlpr3(m, x)
Performs the operation. Takes m, x.
K-Nearest Neighbors
mlnkn(k)
Performs the operation. Takes k.
mlftk(m, x, y)
Performs the operation. Takes m, x, y.
mlpr0(m, xi)
Performs the operation. Takes m, xi.
Naive Bayes
mlnnb()
Performs the operation.
mlftn(m, x, y)
Performs the operation. Takes m, x, y.
mlpr5(m, xi)
Performs the operation. Takes m, xi.
SVM (Simplified)
mlnsv(c)
Performs the operation. Takes c.
PCA
mlpca(x, ncomp)
Performs the operation. Takes x, ncomp.
Metrics
mlac(y, pr)
Performs the operation. Takes y, pr.
mlpr(y, pr, cls)
Processes or prints. Takes y, pr, cls.
mlmse(y, pr)
Sets a value. Takes y, pr.
mlrms(y, pr)
Performs the operation. Takes y, pr.
mlmae(y, pr)
Performs the operation. Takes y, pr.
mlr2(y, pr)
Performs the operation. Takes y, pr.
Cross validation
mlcv(m, x, y, folds, fn)
Performs the operation. Takes m, x, y, folds, fn.
Grid search
mlgrd(m, x, y, grid)
Reads data. Takes m, x, y, grid.
Feature importance
mlimp(m, names)
Performs the operation. Takes m, names.
Save/Load
mlsve(m, path)
Performs the operation. Takes m, path.
mllod(path)
Performs the operation. Takes path.
Pipeline
mlppe(steps)
Performs the operation. Takes steps.
Ensemble
mlens(mds, wts)
Performs the operation. Takes mds, wts.
mlprd(m, x)
Reads data. Takes m, x.
Notes
- Machine learning primitives - linear regression, k-means, decision trees.