test 2d gaussian ...
mean:

m =

    -1
     2

covariance:

cv =

     5     1
     1     1

estimated mean:

est_m =

   -0.9957
    1.9654

estimated covariance:

est_cv =

    5.6694    1.3665
    1.3665    1.1374

test 1d gaussian ...
mean:

m =

     2

covariance:

v =

     4


est_m =

    2.0027


est_v =

    3.9688

estimated mean:

est_m =

    2.0027

estimated covariance:

est_v =

    3.9688

test data i/o ...

feature =

    0.0523    0.0738    0.0031    0.0246    0.0462
    0.0708    0.0154    0.0215    0.0431    0.0492
    0.0123    0.0185    0.0400    0.0615    0.0677
    0.0308    0.0369    0.0585    0.0646    0.0092
    0.0338    0.0554    0.0769    0.0062    0.0277


feature =

    0.0523    0.0738    0.0031    0.0246    0.0462
    0.0708    0.0154    0.0215    0.0431    0.0492
    0.0123    0.0185    0.0400    0.0615    0.0677
    0.0308    0.0369    0.0585    0.0646    0.0092
    0.0338    0.0554    0.0769    0.0062    0.0277


label =

     1
     2
     3
     4
     5

uniformly distributed random data ...
test 2d gaussian ...
mean:
m =
    -1
     2
covariance:
cv =
     5     1
     1     1
estimated mean:
est_m =
   -0.7935
    2.0433
estimated covariance:
est_cv =
    4.6404    0.9272
    0.9272    0.8646
test 1d gaussian ...
mean:
m =
     2
covariance:
v =
     4
est_m =
    2.0597
est_v =
    4.1261
estimated mean:
est_m =
    2.0597
estimated covariance:
est_v =
    4.1261
test data i/o ...
feature =
    0.0523    0.0738    0.0031    0.0246    0.0462
    0.0708    0.0154    0.0215    0.0431    0.0492
    0.0123    0.0185    0.0400    0.0615    0.0677
    0.0308    0.0369    0.0585    0.0646    0.0092
    0.0338    0.0554    0.0769    0.0062    0.0277
??? Error: File: F:\ttng\gradient-rtf\spr_read_data.m Line: 1 Column: 19
"]" expected, "identifier" found.

Error in ==> F:\ttng\gradient-rtf\test_spr.m
On line 90  ==> [feature,label] = spr_read_data(filename)

fschange('F:\ttng\gradient-rtf\spr_read_data.m');
clear spr_read_data
close all
test_spr
test 2d gaussian ...
mean:
m =
    -1
     2
covariance:
cv =
     5     1
     1     1
estimated mean:
est_m =
   -0.9519
    1.9983
estimated covariance:
est_cv =
    4.8940    0.9668
    0.9668    1.0943
test 1d gaussian ...
mean:
m =
     2
covariance:
v =
     4
est_m =
    1.9851
est_v =
    4.0010
estimated mean:
est_m =
    1.9851
estimated covariance:
est_v =
    4.0010
test data i/o ...
feature =
    0.0523    0.0738    0.0031    0.0246    0.0462
    0.0708    0.0154    0.0215    0.0431    0.0492
    0.0123    0.0185    0.0400    0.0615    0.0677
    0.0308    0.0369    0.0585    0.0646    0.0092
    0.0338    0.0554    0.0769    0.0062    0.0277
feature =
    0.0523    0.0738    0.0031    0.0246    0.0462
    0.0708    0.0154    0.0215    0.0431    0.0492
    0.0123    0.0185    0.0400    0.0615    0.0677
    0.0308    0.0369    0.0585    0.0646    0.0092
    0.0338    0.0554    0.0769    0.0062    0.0277
label =
     1
     2
     3
     4
     5
uniformly distributed random data ...
