Changeset 10198:f42413e84a84 in orange
 Timestamp:
 02/13/12 16:51:30 (2 years ago)
 Branch:
 default
 File:

 1 edited
Legend:
 Unmodified
 Added
 Removed

Orange/evaluation/scoring.py
r10196 r10198 1101 1101 1102 1102 def frange(start, end=None, inc=None): 1103 " A range function, that does accept float increments..."1103 """A range function, that does accept float increments...""" 1104 1104 1105 1105 if end is None: … … 1265 1265 1266 1266 results = [] 1267 P, N = tots[1], tots[0]1268 1267 1269 1268 bins = 10 ## divide interval between 0.0 and 1.0 into N bins … … 1366 1365 1367 1366 if res.number_of_iterations>1: 1368 CDTs = [CDT() for iin range(res.number_of_learners)]1367 CDTs = [CDT() for _ in range(res.number_of_learners)] 1369 1368 iterationExperiments = split_by_iterations(res) 1370 1369 for exp in iterationExperiments: … … 1619 1618 1620 1619 aucs = [[[] for _ in range(numberOfClasses)] for _ in range(number_of_learners)] 1621 prob = class_probabilities_from_res(res)1622 1620 1623 1621 for classIndex1 in range(numberOfClasses): … … 2156 2154 2157 2155 lines = None 2158 sums = sorted(sums)2159 2156 2160 2157 linesblank = 0 … … 2240 2237 2241 2238 import numpy 2242 2239 tick = None 2243 2240 for a in list(numpy.arange(lowv, highv, 0.5)) + [highv]: 2244 2241 tick = smalltick … … 2326 2323 """ 2327 2324 accuracies = [0.0]*res.number_of_learners 2328 label_num = len(res.labels)2329 2325 example_num = gettotsize(res) 2330 2326 … … 2354 2350 """ 2355 2351 precisions = [0.0]*res.number_of_learners 2356 label_num = len(res.labels)2357 2352 example_num = gettotsize(res) 2358 2353 … … 2381 2376 """ 2382 2377 recalls = [0.0]*res.number_of_learners 2383 label_num = len(res.labels)2384 2378 example_num = gettotsize(res) 2385 2379
Note: See TracChangeset
for help on using the changeset viewer.