In [10]:

    

import pickle
from pforest.master import master
m=master(dsetname='testCS213')
m.reset()
m.train()
with open('train/out_tree.pic', 'wb') as pickleFile:
    pickle.dump(m.root, pickleFile, pickle.HIGHEST_PROTOCOL)


    

    




master>>init() dsetname: testCS213
master>> create dview
master>> init engine
Found pforest
debug:master:__init__: ['train/dataset00.pic', 'train/dataset01.pic', 'train/dataset02.pic', 'train/dataset03.pic']
master>> init local variables
master>>reset()
master>>reset() H: 2.9537
master>>reset() Q: 03060
master::train() node20*-
master::train() node19R-
master::train() node18R-
master::train() node17R-
master::train() node16R-
master::train() node15RQ
master::train() node15LQ
master::train() node16L-
master::train() node15RQ
master::train() node15L-
master::train() node14RQ
master::train() node14L-
master::train() node13R-
master::train() node12RQ
master::train() node12LQ
master::train() node13LQ
master::train() node17L-
master::train() node16R-
master::train() node15R-
master::train() node14R-
master::train() node13RQ
master::train() node13LQ
master::train() node14LG
master::train() node15L-
master::train() node14RQ
master::train() node14L-
master::train() node13RQ
master::train() node13LQ
master::train() node16L-
master::train() node15RQ
master::train() node15L-
master::train() node14RQ
master::train() node14L-
master::train() node13RQ
master::train() node13L-
master::train() node12RQ
master::train() node12L-
master::train() node11R-
master::train() node10RQ
master::train() node10LQ
master::train() node11L-
master::train() node10RQ
master::train() node10LQ
master::train() node18LQ
master::train() node19L-
master::train() node18R-
master::train() node17RQ
master::train() node17LQ
master::train() node18L-
master::train() node17RG
master::train() node17LQ

In [12]:

    

from pforest.dataset import dataset
from pforest.tree import tree
with open('train/out_tree.pic', 'rb') as pickleFile:
    root = pickle.load(pickleFile)
#init the test tree
t=tree()
t.settree(root)
t.show()


    

    




Found pforest
*- 20 H:2.954e+00,Q:003060 tau:9.0 theta:[ 20.]
L- 19 H:2.644e+00,Q:000744 tau:9.0 theta:[ 102.]
L- 18 H:2.495e+00,Q:000524 tau:5.0 theta:[ 125.]
LQ 17 H:2.127e+00,Q:000064 (cl,P):(007,0.31) (006,0.31) (008,0.19)
RG 17 H:2.438e+00,Q:000460 (cl,P):(008,0.25) (009,0.23) (006,0.21)
R- 18 H:2.481e+00,Q:000220 tau:9.0 theta:[ 47.]
LQ 17 H:2.536e+00,Q:000172 (cl,P):(009,0.28) (008,0.23) (010,0.21)
RQ 17 H:1.281e+00,Q:000048 (cl,P):(009,0.58) (010,0.33) (013,0.08)
R- 19 H:2.941e+00,Q:002316 tau:7.0 theta:[ 99.]
LQ 18 H:2.327e+00,Q:000108 (cl,P):(006,0.41) (009,0.22) (007,0.15)
R- 18 H:2.939e+00,Q:002208 tau:11.0 theta:[ 19.]
L- 17 H:2.761e+00,Q:001540 tau:9.0 theta:[ 22.]
L- 16 H:2.708e+00,Q:000764 tau:10.0 theta:[ 31.]
L- 15 H:2.577e+00,Q:000660 tau:11.0 theta:[ 199.]
L- 14 H:2.529e+00,Q:000632 tau:8.0 theta:[ 29.]
L- 13 H:2.409e+00,Q:000564 tau:9.0 theta:[ 199.]
L- 12 H:2.346e+00,Q:000412 tau:10.0 theta:[ 154.]
L- 11 H:2.236e+00,Q:000208 tau:11.0 theta:[ 171.]
LQ 10 H:2.281e+00,Q:000188 (cl,P):(009,0.36) (008,0.28) (007,0.13)
RQ 10 H:1.371e+00,Q:000020 (cl,P):(009,0.60) (008,0.20) (007,0.20)
R- 11 H:2.209e+00,Q:000204 tau:9.0 theta:[ 160.]
LQ 10 H:2.095e+00,Q:000124 (cl,P):(006,0.42) (007,0.29) (009,0.13)
RQ 10 H:1.959e+00,Q:000080 (cl,P):(008,0.35) (009,0.25) (007,0.20)
RQ 12 H:1.902e+00,Q:000152 (cl,P):(006,0.61) (007,0.13) (010,0.08)
RQ 13 H:2.486e+00,Q:000068 (cl,P):(009,0.29) (007,0.29) (010,0.12)
RQ 14 H:2.236e+00,Q:000028 (cl,P):(009,0.29) (008,0.29) (012,0.14)
RQ 15 H:2.378e+00,Q:000104 (cl,P):(010,0.27) (011,0.23) (009,0.19)
R- 16 H:2.497e+00,Q:000776 tau:10.0 theta:[ 20.]
L- 15 H:2.284e+00,Q:000344 tau:10.0 theta:[ 34.]
L- 14 H:2.064e+00,Q:000320 tau:6.0 theta:[ 125.]
LQ 13 H:2.261e+00,Q:000160 (cl,P):(009,0.40) (008,0.28) (007,0.12)
RQ 13 H:1.692e+00,Q:000160 (cl,P):(009,0.60) (010,0.17) (008,0.15)
RQ 14 H:1.918e+00,Q:000024 (cl,P):(012,0.33) (011,0.33) (013,0.17)
R- 15 H:2.493e+00,Q:000432 tau:11.0 theta:[ 20.]
LG 14 H:2.486e+00,Q:000204 (cl,P):(010,0.31) (009,0.29) (008,0.14)
R- 14 H:2.316e+00,Q:000228 tau:7.0 theta:[ 191.]
LQ 13 H:2.463e+00,Q:000088 (cl,P):(009,0.32) (010,0.27) (011,0.14)
RQ 13 H:2.023e+00,Q:000140 (cl,P):(009,0.34) (011,0.31) (010,0.20)
R- 17 H:2.901e+00,Q:000668 tau:12.0 theta:[ 19.]
L- 16 H:2.983e+00,Q:000400 tau:10.0 theta:[ 34.]
L- 15 H:2.988e+00,Q:000392 tau:8.0 theta:[ 126.]
L- 14 H:2.920e+00,Q:000340 tau:8.0 theta:[ 160.]
LQ 13 H:2.793e+00,Q:000132 (cl,P):(010,0.21) (007,0.18) (006,0.18)
R- 13 H:2.529e+00,Q:000208 tau:12.0 theta:[ 190.]
LQ 12 H:2.422e+00,Q:000152 (cl,P):(009,0.32) (010,0.26) (013,0.18)
RQ 12 H:2.414e+00,Q:000056 (cl,P):(009,0.29) (011,0.21) (007,0.21)
RQ 14 H:2.412e+00,Q:000052 (cl,P):(012,0.31) (011,0.23) (013,0.15)
RQ 15 H:1.000e+00,Q:000008 (cl,P):(011,0.50) (010,0.50) (013,0.00)
R- 16 H:2.322e+00,Q:000268 tau:11.0 theta:[ 162.]
LQ 15 H:2.456e+00,Q:000128 (cl,P):(013,0.28) (012,0.22) (011,0.16)
RQ 15 H:2.073e+00,Q:000140 (cl,P):(013,0.40) (012,0.23) (010,0.20)

In [13]:

    

import numpy as np
u=np.zeros(203)
Prob=t.classify(u)


    

In [14]:

    

Prob


    

    
Out[14]:





array([ 0.    ,  0.    ,  0.    ,  0.    ,  0.    ,  0.0625,  0.3125,
        0.3125,  0.1875,  0.    ,  0.    ,  0.125 ,  0.    ,  0.    ])

In [15]:

    

predictedGrade=np.argmax(Prob)


    

In [17]:

    

Grade=['A', 'B+', 'B', 'C+', 'C' , 'D+' , 'D' , 'F' , 'W' , 'S' , 'S#' , 'U' , 'U#']
Grade[predictedGrade]


    

    
Out[17]:





'D'

In [ ]: