def plotpoints_knn_fm_fires():
fm = amf.ForwardMapping(amf.regression.kNN, [55], 3)
data = amf.data.load('../data/fires.txt')
subset = amf.data.random_subsets(data, [400])[0]
fm.train(subset)
for x in misc.xfrange(45.0, 75.0, .1):
print x, fm.predict((x,))[0]
def plotpoints_knn_fm_fires():
data = amf.data.load('../data/fires.txt')
subset = amf.data.random_subsets(data, [200])[0]
for k in range(5, 30, 5):
fm = amf.ForwardMapping(amf.regression.kNN, [k], 1)
fm.train(subset)
out = open('../data/plots/fires_knn_graph/k=%d' % k, 'w')
for x in misc.xfrange(45.0, 75.0, .1):
print >> out, x, fm.predict((x,))[0]
gpscript = open('../data/plots/fires_knn_graph/plot.gp' ,'w')
print >> gpscript, """
def plotpoints_loess_fm_fires():
data = amf.data.load('../data/fires.txt')
subset = amf.data.random_subsets(data, [200])[0]
window = .5
for i in range(3):
fm = amf.ForwardMapping(amf.regression.LOESS, [window, 1], 1)
fm.train(subset)
out = open('../data/plots/fires_loess_graph/window=%.1f' % window, 'w')
for x in misc.xfrange(45.0, 75.0, .1):
print >> out, x, fm.predict((x,))[0]
window += .5
gpscript = open('../data/plots/fires_loess_graph/plot.gp' ,'w')
print >> gpscript, """
