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|
res_dir="$tmpdir/dir-eval"
mkdir -p "$res_dir"
export PATH="$(pwd):$PATH"
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -O "$res_dir/errors.txt" -n5 matrix.libsvm >/dev/null
sort "$res_dir/errors.txt" |
cmp 'heri-eval #1 -O' \
'#14 1 0 0.9799999999999999
#28 0 1 0.9599999999999999
#29 0 1 0.9399999999999997
#30 0 1 0.9199999999999998
#32 0 1 0.8999999999999997
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -o "$res_dir/results.txt" -n5 matrix.libsvm >/dev/null
awk 'NR == 14 || NR == 28' "$res_dir/results.txt" |
cmp 'heri-eval #2 -o' \
'1 0 0.9799999999999999
0 1 0.9599999999999999
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -m "$res_dir/confusion_matrix.txt" -n5 matrix.libsvm >/dev/null
cat "$res_dir/confusion_matrix.txt" |
cmp 'heri-eval #3 -m' \
'4 : 0 1
1 : 1 0
'
heri-eval -h 2>&1 | sed -n 's/^usage:.*/usage:/p' |
cmp 'heri-eval #4 -h' \
'usage:
'
{ heri-eval 2>&1; echo ex=$?; } |
cmp 'heri-eval #5 no args' \
'Either -n or -r or -e must be specified, run heri-eval -h for details
ex=1
'
rm $res_dir/*
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -e matrix_test.libsvm \
-o "$res_dir/results.txt" \
-m "$res_dir/confusion_matrix.txt" \
-O "$res_dir/errors.txt" matrix.libsvm 2>&1 |
cmp 'heri-eval #6 -e' \
'Total statistics
Class 0 P, R, F1: 0.75 3/4 , 0.5 3/6 , 0.6
Class 1 P, R, F1: 0.5714 4/7 , 0.8 4/5 , 0.6667
Accuracy : 0.6364 7/11
Macro average P, R, F1: 0.6607 , 0.65 , 0.6333
'
cat "$res_dir/results.txt" "$res_dir/confusion_matrix.txt" "$res_dir/errors.txt" |
awk 'BEGIN {OFMT="%0.6g"} /:/ {print; next} {printf "%s %s %0.6g\n", $1, $2, $3}' |
cmp 'heri-eval #6.1 -e + -o + -O + -m' \
'1 1 0.25
1 1 0.375
1 0 0.98
1 1 0.5
1 1 0.625
0 0 0.25
0 1 0.96
0 1 0.94
0 1 0.92
0 0 0.125
0 0 0
3 : 0 1
1 : 1 0
#3 1 0
#7 0 1
#8 0 1
#9 0 1
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -S 100500 -f -n5 matrix.libsvm | awk 'NR==1, /^Total/' |
cmp 'heri-eval #7 -S 100500 -f' \
'Fold 1x1 statistics
Class 0 P, R, F1: 1 6/6 , 0.75 6/8 , 0.8571
Class 1 P, R, F1: 0.75 6/8 , 1 6/6 , 0.8571
Accuracy : 0.8571 12/14
Macro average P, R, F1: 0.875 , 0.875 , 0.8571
Fold 1x2 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8571 6/7 , 1 6/6 , 0.9231
Accuracy : 0.9286 13/14
Macro average P, R, F1: 0.9286 , 0.9375 , 0.9282
Fold 1x3 statistics
Class 0 P, R, F1: 0.8889 8/9 , 1 8/8 , 0.9412
Class 1 P, R, F1: 1 5/5 , 0.8333 5/6 , 0.9091
Accuracy : 0.9286 13/14
Macro average P, R, F1: 0.9444 , 0.9167 , 0.9251
Fold 1x4 statistics
Class 0 P, R, F1: 1 8/8 , 1 8/8 , 1
Class 1 P, R, F1: 1 6/6 , 1 6/6 , 1
Accuracy : 1 14/14
Macro average P, R, F1: 1 , 1 , 1
Fold 1x5 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8333 5/6 , 1 5/5 , 0.9091
Accuracy : 0.9231 12/13
Macro average P, R, F1: 0.9167 , 0.9375 , 0.9212
Total statistics
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -S 100500 -p '-mr' -n5 matrix.libsvm |
cmp 'heri-eval #8 -p' \
'Total statistics
Class 0 P, R, F1: 0.973 36/37 , 0.9 36/40 , 0.9351
Class 1 P, R, F1: 0.875 28/32 , 0.9655 28/29 , 0.918
Accuracy : 0.9275 64/69
Total cross-folds statistics
Class 0 P> mean, maxdev, stddev : 97.8 8.89 4.97
Class 1 P> mean, maxdev, stddev : 88.8 13.8 11.0
Class 0 R> mean, maxdev, stddev : 90.0 15.0 10.5
Class 1 R> mean, maxdev, stddev : 96.7 13.3 7.45
Class 0 F1> mean, maxdev, stddev : 93.3 7.59 5.08
Class 1 F1> mean, maxdev, stddev : 92.0 8.03 5.15
A> mean, maxdev, stddev : 92.7 7.25 5.06
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -S 100500 -p '-mr' -n5 -f -t2 matrix.libsvm |
cmp 'heri-eval #8.1 -p -t2' \
'Fold 1x1 statistics
Class 0 P, R, F1: 1 6/6 , 0.75 6/8 , 0.8571
Class 1 P, R, F1: 0.75 6/8 , 1 6/6 , 0.8571
Accuracy : 0.8571 12/14
Fold 1x2 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8571 6/7 , 1 6/6 , 0.9231
Accuracy : 0.9286 13/14
Fold 1x3 statistics
Class 0 P, R, F1: 0.8889 8/9 , 1 8/8 , 0.9412
Class 1 P, R, F1: 1 5/5 , 0.8333 5/6 , 0.9091
Accuracy : 0.9286 13/14
Fold 1x4 statistics
Class 0 P, R, F1: 1 8/8 , 1 8/8 , 1
Class 1 P, R, F1: 1 6/6 , 1 6/6 , 1
Accuracy : 1 14/14
Fold 1x5 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8333 5/6 , 1 5/5 , 0.9091
Accuracy : 0.9231 12/13
Fold 2x1 statistics
Class 0 P, R, F1: 1 8/8 , 1 8/8 , 1
Class 1 P, R, F1: 1 6/6 , 1 6/6 , 1
Accuracy : 1 14/14
Fold 2x2 statistics
Class 0 P, R, F1: 1 8/8 , 1 8/8 , 1
Class 1 P, R, F1: 1 6/6 , 1 6/6 , 1
Accuracy : 1 14/14
Fold 2x3 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8571 6/7 , 1 6/6 , 0.9231
Accuracy : 0.9286 13/14
Fold 2x4 statistics
Class 0 P, R, F1: 1 7/7 , 0.875 7/8 , 0.9333
Class 1 P, R, F1: 0.8571 6/7 , 1 6/6 , 0.9231
Accuracy : 0.9286 13/14
Fold 2x5 statistics
Class 0 P, R, F1: 0.8571 6/7 , 0.75 6/8 , 0.8
Class 1 P, R, F1: 0.6667 4/6 , 0.8 4/5 , 0.7273
Accuracy : 0.7692 10/13
Total statistics
Class 0 P, R, F1: 0.973 72/74 , 0.9 72/80 , 0.9351
Class 1 P, R, F1: 0.875 56/64 , 0.9655 56/58 , 0.918
Accuracy : 0.9275 128/138
Total cross-folds statistics
Class 0 P> mean, maxdev, stddev : 97.5 11.7 5.41
Class 1 P> mean, maxdev, stddev : 88.2 21.5 11.7
Class 0 R> mean, maxdev, stddev : 90.0 15.0 9.86
Class 1 R> mean, maxdev, stddev : 96.3 16.3 7.77
Class 0 F1> mean, maxdev, stddev : 93.3 13.3 6.41
Class 1 F1> mean, maxdev, stddev : 91.7 19.0 8.20
A> mean, maxdev, stddev : 92.6 15.7 7.13
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -M tfc -S 100 -n2 matrix.libsvm 2>&1 |
cmp 'heri-eval #9.1 -M tfc' \
'Fold 1x1 statistics
Class 0 P, R, F1: 0.95 19/20 , 0.95 19/20 , 0.95
Class 1 P, R, F1: 0.9333 14/15 , 0.9333 14/15 , 0.9333
Accuracy : 0.9429 33/35
Macro average P, R, F1: 0.9417 , 0.9417 , 0.9417
Fold 1x2 statistics
Class 0 P, R, F1: 1 17/17 , 0.85 17/20 , 0.9189
Class 1 P, R, F1: 0.8235 14/17 , 1 14/14 , 0.9032
Accuracy : 0.9118 31/34
Macro average P, R, F1: 0.9118 , 0.925 , 0.9111
Total statistics
Class 0 P, R, F1: 0.973 36/37 , 0.9 36/40 , 0.9351
Class 1 P, R, F1: 0.875 28/32 , 0.9655 28/29 , 0.918
Accuracy : 0.9275 64/69
Macro average P, R, F1: 0.924 , 0.9328 , 0.9265
Total cross-folds statistics
Macro average P> mean, maxdev, stddev : 92.7 1.50 2.11
Class 0 P> mean, maxdev, stddev : 97.5 2.50 3.54
Class 1 P> mean, maxdev, stddev : 87.8 5.49 7.76
Macro average R> mean, maxdev, stddev : 93.3 0.833 1.18
Class 0 R> mean, maxdev, stddev : 90.0 5.00 7.07
Class 1 R> mean, maxdev, stddev : 96.7 3.33 4.71
Macro average F1> mean, maxdev, stddev : 92.6 1.53 2.16
Class 0 F1> mean, maxdev, stddev : 93.4 1.55 2.20
Class 1 F1> mean, maxdev, stddev : 91.8 1.51 2.13
A> mean, maxdev, stddev : 92.7 1.55 2.20
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -n2 matrix.libsvm 2>&1 |
cmp 'heri-eval #9.2 -Mt' \
'Total statistics
Class 0 P, R, F1: 0.973 36/37 , 0.9 36/40 , 0.9351
Class 1 P, R, F1: 0.875 28/32 , 0.9655 28/29 , 0.918
Accuracy : 0.9275 64/69
Macro average P, R, F1: 0.924 , 0.9328 , 0.9265
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -M tf -S 100 -n2 matrix.libsvm 2>&1 |
cmp 'heri-eval #9.3 -M tf' \
'Fold 1x1 statistics
Class 0 P, R, F1: 0.95 19/20 , 0.95 19/20 , 0.95
Class 1 P, R, F1: 0.9333 14/15 , 0.9333 14/15 , 0.9333
Accuracy : 0.9429 33/35
Macro average P, R, F1: 0.9417 , 0.9417 , 0.9417
Fold 1x2 statistics
Class 0 P, R, F1: 1 17/17 , 0.85 17/20 , 0.9189
Class 1 P, R, F1: 0.8235 14/17 , 1 14/14 , 0.9032
Accuracy : 0.9118 31/34
Macro average P, R, F1: 0.9118 , 0.925 , 0.9111
Total statistics
Class 0 P, R, F1: 0.973 36/37 , 0.9 36/40 , 0.9351
Class 1 P, R, F1: 0.875 28/32 , 0.9655 28/29 , 0.918
Accuracy : 0.9275 64/69
Macro average P, R, F1: 0.924 , 0.9328 , 0.9265
'
env SVM_TRAIN_CMD=test_train SVM_PREDICT_CMD=test_predict \
heri-eval -Mt -n2 matrix.libsvm -- -0 2>&1 |
cmp 'heri-eval #10.1 -- options' \
'Total statistics
Class 0 P, R, F1: 0.5797 40/69 , 1 40/40 , 0.7339
Class 1 P, R, F1: 0 0/0 , 0 0/29 , 0
Accuracy : 0.5797 40/69
Macro average P, R, F1: 0.2899 , 0.5 , 0.367
'
env SVM_TRAIN_CMD=test_train SVM_PREDICT_CMD=test_predict \
heri-eval -Mt -n2 matrix.libsvm -- -1 2>&1 |
cmp 'heri-eval #10.2 -- options' \
'Total statistics
Class 0 P, R, F1: 0 0/0 , 0 0/40 , 0
Class 1 P, R, F1: 0.4203 29/69 , 1 29/29 , 0.5918
Accuracy : 0.4203 29/69
Macro average P, R, F1: 0.2101 , 0.5 , 0.2959
'
env SVM_TRAIN_CMD=test_train SVM_PREDICT_CMD=test_predict \
heri-eval -Mt -s '-r' -S117 -n2 matrix.libsvm -- -1 2>&1 |
cmp 'heri-eval #10.3 -- options' \
'Total statistics
Class 0 P, R, F1: 0 0/0 , 0 0/40 , 0
Class 1 P, R, F1: 0.4203 29/69 , 1 29/29 , 0.5918
Accuracy : 0.4203 29/69
Macro average P, R, F1: 0.2101 , 0.5 , 0.2959
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -r 70 matrix.libsvm 2>&1 |
cmp 'heri-eval #10.4 -- options' \
'Total statistics
Class 0 P, R, F1: 1 10/10 , 0.8333 10/12 , 0.9091
Class 1 P, R, F1: 0.8182 9/11 , 1 9/9 , 0.9
Accuracy : 0.9048 19/21
Macro average P, R, F1: 0.9091 , 0.9167 , 0.9045
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -r 70 matrix.libsvm 2>&1 |
cmp 'heri-eval #10.4 -- options' \
'Total statistics
Class 0 P, R, F1: 1 10/10 , 0.8333 10/12 , 0.9091
Class 1 P, R, F1: 0.8182 9/11 , 1 9/9 , 0.9
Accuracy : 0.9048 19/21
Macro average P, R, F1: 0.9091 , 0.9167 , 0.9045
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -e matrix_test2.libsvm matrix.libsvm 2>&1 |
cmp 'heri-eval #11.1 -- options' \
'Total statistics
Class 0 P, R, F1: 0.9091 60/66 , 0.9677 60/62 , 0.9375
Class 1 P, R, F1: 0.9636 53/55 , 0.8983 53/59 , 0.9298
Accuracy : 0.9339 113/121
Macro average P, R, F1: 0.9364 , 0.933 , 0.9337
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -T-100 -e matrix_test2.libsvm matrix.libsvm 2>&1 |
cmp 'heri-eval #11.2 -- options' \
'Total statistics
Class 0 P, R, F1: 0.9091 60/66 , 0.9677 60/62 , 0.9375
Class 1 P, R, F1: 0.9636 53/55 , 0.8983 53/59 , 0.9298
Micro average P, R, F1: 0.9339 113/121 , 0.9339 113/121 , 0.9339
Macro average P, R, F1: 0.9364 , 0.933 , 0.9337
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -T0 -e matrix_test2.libsvm matrix.libsvm 2>&1 |
cmp 'heri-eval #11.3 -- options' \
'Total statistics
Class 0 P, R, F1: 0.9091 60/66 , 0.9677 60/62 , 0.9375
Class 1 P, R, F1: 0.9636 53/55 , 0.8983 53/59 , 0.9298
Micro average P, R, F1: 0.9339 113/121 , 0.9339 113/121 , 0.9339
Macro average P, R, F1: 0.9364 , 0.933 , 0.9337
'
env SVM_TRAIN_CMD=true SVM_PREDICT_CMD=rulebased_predict \
heri-eval -Mt -S 100 -T0.1 -e matrix_test2.libsvm matrix.libsvm 2>&1 |
cmp 'heri-eval #11.2 -- options' \
'Total statistics
Class 0 P, R, F1: 1 47/47 , 0.7581 47/62 , 0.8624
Class 1 P, R, F1: 1 47/47 , 0.7966 47/59 , 0.8868
Micro average P, R, F1: 1 94/94 , 0.7769 94/121 , 0.8744
Macro average P, R, F1: 1 , 0.7773 , 0.8746
'
|
