def runlmpla(n=10):
import pla as p
fw = genline()
(X,y) = genxy(n, fw)
wini = lm(X,y)
errratio = geterr(X,y,wini)
# use the initial weights from regression
res = p.pla(X[:,(1,2)], y, w=wini[1:3], b=wini[0])
# target function values
res['lmw'] = wini
res['fw'] = fw[1:3]
res['fb'] = fw[0]
return(res)
def runlmpla(n=10):
import pla as p
fw = genline()
(X, y) = genxy(n, fw)
wini = lm(X, y)
errratio = geterr(X, y, wini)
# use the initial weights from regression
res = p.pla(X[:, (1, 2)], y, w=wini[1:3], b=wini[0])
# target function values
res['lmw'] = wini
res['fw'] = fw[1:3]
res['fb'] = fw[0]
return (res)
def naive_pla(points):
from pla import pla
return pla(points)
def naive_pla(points):
from pla import pla
return pla(points)
