craigacp / mitoolbox Goto Github PK

how to store and use it in google colab with the use of google drive?

The code gets to the following error while running MIToolbox on uint8 data types:
"Out of memory. Type HELP MEMORY for your options."

However it works well with double data type.

Readme provides the result as 0.02, is there any normalization or what influence the result?

x = np.array([1,1,1,0,0])
y=np.array([1,0,1,1,0])
mutual_info_score(x,y)
0.013844293808390418

I compiled the matlab sources for MIToolbox using MATLAB R2016b and gcc 4.9.1, but I get the following error when running your examples to test:

>> y = [1 1 1 0 0]';
>> x = [1 0 1 1 0]';
>> joint([x,y])
Not enough input arguments.

Error in joint (line 12)
if (~isa(X,'double') || ~isa(arities,'double'))

The other examples worked fine. This is based on your latest release, 3.0.1.

Hey,

just for you to know: I wrote something similar to the MIToolbox for Python. If you are interested, please have a look at https://github.com/tud-zih-energy/pymit.

Best,

Andreas

Hi Adam,

I have 500 examples, continues outcome ( above and below 0) and 33000 features. I would like to use feast,... for finding the most informative features. As far as I know, I have to discretise the outcome. Can you please advise how I should that? Also do you aware of any information theoretic packages that can deal with the continues outcome?

Please see some of numbers in the list for the outcome.

0.55228076
-0.3197724
0.58774863
-0.5174945
-0.173138
1.27375815
0.78408593
0.74372201
-1.3886196
0.43545769
-0.0689654
0.18626918
1.8202002
0.10355088
-0.0560193
0.29268956
-0.4401979
1.61399178
-0.704535
0.00430693
1.41157343
-0.0646488
-1.4474665
0.4307273
0.44970806
-0.3885697
1.10758465
-0.1339137
0.12522725
-0.3379575
-1.099666
0.31524279
-0.7666343
0.22144974
-0.8017797
-1.1909404
-0.7958541
-1.5830851
1.03128861
-1.0312886
-1.736507
0.77242535
1.06106625
0.95375794
-0.8626751
-0.4025419
-0.1078819
0.71006597
0.5422753
-2.2562499
-1.3238074
-1.919012
1.24519952
-0.4930275
0.47848871
1.21762188
-0.6239719
1.42333462
-0.0086139
0.89435119
-1.698852
1.77679865
-0.038772
-0.2569066
0.28371043
-0.360848
-0.2658198
0.8440787
-0.9812682
0.67719571
0.31977237
-2.0077154
0.48332361
0.70453501
0.52242483
-0.9537579
-0.8197281
-1.2835121
-0.5076713
0.35625516
0.03015302
0.05601926
-0.1994326
1.13176806
-2.3148972
1.3886196
0.5724601
-1.8925387
-1.1822326
-0.2926896
0.37467286
-0.6610331
-0.2971879
-1.3555018
-1.5536207
0.73805488
-0.3746729
-0.6031758
-0.6935372
1.43529606
1.48532767
0.629213
0.19943255
-0.7211937
-1.068659
-0.4165933
0.01292112
1.26412388
-0.9335899
0.22586574
-2.2044686
-0.6450414
-0.5724601
1.00954199
0.05170609
-1.0840322
-0.5027781
-0.7782424
-0.2258657
-0.5623418
-0.1644006
-0.7156187
-0.8879448
-0.2792295
-0.0776024
-0.4544784
-0.8137162
0.93358993
0.73241136
1.89253869
-1.366375
-1.472472
0.15131773
-0.6135407
-0.1165502
0.80177968
0.92695117
1.71737513
0.77824241
-1.4853277
-0.2347111
-0.5522808
0.85644338
0.09922176
-0.5573042
-1.1566322
0.34252111
0.37005675
1.51180219
-1.5118022
0.02153627
0.37929696
1.28351212
-0.0948945
-0.7551286
1.59834762
0.14696264
-0.4784887
1.56818275
0.60317579
0.82576977
1.05353422
0.33795753
0.83184174
-2.702943
-0.3107197
0.72679107
1.40000431
-0.379297
-0.2702843
-0.4307273
1.18223265
0.3516698
1.13997784
1.73650701
0.60835006
1.47247197
0.03446219
1.55362072
-0.5224248
1.06865897
2.46384107
0.38856968
-0.333401
0.18188866
2.31489724
-0.3654485
-0.5422753
1.36637495
-0.112215
-0.3152428
0.42600652
-0.1426103
0.94027009
-0.7899563
-0.5472712
0.39787592
1.25460554
-1.3135329
0.42129522
0.12088759
0.86267505
0.99530565
-1.4233346
0.97432155
0.19065327
0.26581978
-0.6664013
-2.158
0.9007945
0.0776024
-0.3016924
-1.9763958
0.27475411
1.08403222
0.81972809
0.23028616
2.00771543
1.33422361
0.55730423
-0.9402701
0.76086887
-0.6083501
0.14261033
-0.4354577
1.6634623
-1.009542
-0.473665
-0.6880696
0.34709182
-1.6634623
0.65035348
-0.3562552
0.92035301
0.85024479
-0.6717887
1.04606148
-0.4978969
0.4544784
-1.680894
-2.1157713
-0.1469626
1.94690278
-2.041138
0.49789692
-1.1650809
0.11655021
-1.1317681
1.03864671
-1.6300412
2.15799996
1.16508088
0.30169235
0.23471108
-2.5652793
0.01722854
-2.382787
0.46885224
-0.8318417
0.038772
2.92573583
0.41659325
0.41190048
0.58263735
-0.2747541
-1.6139918
-0.1687677
-0.0430825
0.78995634
0.40721675
-1.0918158
-1.1236339
-1.2176219
0.25690662
-1.5393809
-0.030153
-1.7562965
1.52544651
-0.9882626
-1.3774121
0.83794453
-0.6771957
0.24801382
-1.4115734
0.27028425
-1.7767986
0.56739369
-2.0770094
-1.2546055
-1.7173751
-0.9007945
-0.2126306
-0.1818887
-1.0763138
-0.3470918
-0.2038279
-1.2086323
0.07328321
0.20822723
-0.8564434
1.09966602
0.96742157
1.97639581
-0.2837104
-0.920353
0.71561873
1.91901198

Thanks
Fari