Warning, this table is very out of date. Most of my algorithms have been improved (some quite significantly) since this table was generated. I am working to generate a new one, but it takes time to run this many tests.
I ran several of my learning algorithms with several datasets to try to determine which algorithm was the
best. I have improved some of the algorithms since I made this table, so don't complain if you get slightly
different results from these numbers. You can repeat any of these experiments with the following command
waffles_learn crossvalidate [dataset] [algorithm]
, where [dataset]
is shown in the top-most row, and [algorithm]
is shown in the
left-most column. (Also, you'll need to append ".arff" to the dataset name to specify the filename.) For
example, if you run the command
waffles_learn crossvalidate abalone.arff baseline
, then you should expect to obtain an accuracy of about 0.16495. The green (next to the
left-most) column shows a "score" for each algorithm. This score was computed as follows:
For each dataset, the predictive accuracy scores were adjusted linearly such that baseline received a score of 0, and the most accurate algorithm received a score of 1. (Thus scores could not exceed 1, and would only be negative if the algorithm did worse than baseline, which shouldn't happen, but unfortunately does sometimes.) These scores were then averaged (excluding any scores less than -1) to produce the overall score for the algorithm.
If you want to understand how to parse the [algorithm]
, take a look at
the usage page for the learn
tool. You should be aware that there are several
known problems with this chart, including:
bag 64 bucket decisiontree meanmarginstree end end
will consistently outperform
bag 16 bucket decisiontree meanmarginstree end end
, but the latter seems to have gotten lucky by failing to
yield results for some of the datasets that would have pulled it down.bag 64 bucket decisiontree meanmarginstree end end
". This algorithm
is published in:Algorithm | Score | abalone | adult-census | anneal | arrhythmia | audiology | autos | badges2 | balance-scale | balloons | breast-cancer | breast-w | bupa | cars | chess | chess-KingRookVKingPawn | colic | colon | credit-a | credit-g | dermatology | diabetes | ecoli | glass | heart-c | heart-h | heart-statlog | hepatitis | hypothyroid | ionosphere | iris | kr-vs-kp | kropt | labor | lenses | letter | lungCancer | lymph | lymphoma | MagicTelescope | mushroom | musk | nursery | ozone | post-operativePatient | primary-tumor | segment | sick | sonar | soybean | spambase | spectrometer | splice | teachingAssistant | titanic | vehicle | vote | vowel | waveform-5000 | wine | yeast | zoo |
baseline | 0 | 0.16495 | 0.75919 | 0.76169 | 0.54204 | 0.21947 | 0.32683 | 0.71429 | 0.44512 | 0.44 | 0.7028 | 0.65522 | 0.57974 | 0.70023 | 0.16228 | 0.5132 | 0.63043 | 0.58387 | 0.55507 | 0.7 | 0.30601 | 0.65104 | 0.4256 | 0.32897 | 0.5446 | 0.63946 | 0.53259 | 0.79357 | 0.92285 | 0.64101 | 0.29067 | 0.5132 | 0.16228 | 0.64938 | 0.625 | 0.03773 | 0.35 | 0.51622 | 0.47917 | 0.64837 | 0.51797 | 0.84586 | 0.33156 | 0.97121 | 0.71111 | 0.24774 | 0.13385 | 0.93876 | 0.5125 | 0.11831 | 0.60595 | 0.087756 | 0.51881 | 0.29398 | 0.67696 | 0.23617 | 0.61383 | 0.16788 | 0.32628 | 0.39888 | 0.31199 | 0.40565 |
neuralnet | 0.3649 | 0.25391 | 0.55174 | 0.61759 | 0.38363 | 0.76814 | 0.16597 | 1 | 0.87584 | 0.96 | 0.68881 | 0.89814 | 0.56066 | 0.89282 | 0.38651 | 0.9776 | 0.41033 | 0.53871 | 0.5458 | 0.4548 | 0.5153 | 0.55156 | 0.85 | 0.24953 | 0.50025 | 0.4381 | 0.50963 | 0.52885 | 0.45668 | 0.84729 | 0.94 | 0.97228 | 0.38214 | 0.56872 | 0.58333 | 0.55662 | 0.4 | 0.79865 | 0.27083 | 0.47065 | 0.99985 | 0.77384 | 0.9208 | 0.74259 | 0.59111 | 0.38351 | 0.13965 | 0.6667 | 0.76731 | 0.91157 | 0.60578 | 0.042925 | 0.93492 | 0.32856 | 0.78455 | 0.24421 | 0.94437 | 0.69414 | 0.84576 | 0.33483 | 0.57358 | 0.91267 |
bucket neuralnet neuralnet -addlayer 4 neuralnet -addlayer 8 -momentum 0.8 neuralnet -addlayer 16 -momentum 0.8 end | 0.40578 | 0.26435 | 0.75919 | 0.76192 | 0.49823 | 0.73717 | 0.30229 | 1 | 0.93184 | 0.65664 | 0.91984 | 0.5259 | 0.97581 | 0.55873 | 0.99011 | 0.61902 | 0.60968 | 0.56319 | 0.6604 | 0.54208 | 0.61589 | 0.84167 | 0.29252 | 0.49375 | 0.54898 | 0.53407 | 0.79356 | 0.92285 | 0.87751 | 0.964 | 0.98817 | 0.5527 | 0.59298 | 0.75 | 0.51709 | 0.40625 | 0.77973 | 0.33958 | 0.62876 | 0.84586 | 0.9764 | 0.97121 | 0.63111 | 0.37936 | 0.24961 | 0.93876 | 0.79135 | 0.91479 | 0.58308 | 0.081358 | 0.94107 | 0.33774 | 0.78755 | 0.25366 | 0.94803 | 0.92303 | 0.83912 | 0.38539 | 0.57264 | 0.91286 | ||
neuralnet -addlayer 4 | 0.41207 | 0.26426 | 0.75919 | 0.76125 | 0.54027 | 0.65929 | 0.32873 | 1 | 0.91744 | 0.96 | 0.64545 | 0.94878 | 0.57969 | 0.95602 | 0.38942 | 0.98849 | 0.60543 | 0.64516 | 0.65826 | 0.7 | 0.53552 | 0.64974 | 0.83512 | 0.32243 | 0.52675 | 0.60408 | 0.50148 | 0.78581 | 0.92285 | 0.86154 | 0.95733 | 0.98611 | 0.39247 | 0.57931 | 0.625 | 0.10892 | 0.4625 | 0.78784 | 0.3875 | 0.64848 | 1 | 0.8462 | 0.96319 | 0.97121 | 0.53778 | 0.32974 | 0.2232 | 0.93876 | 0.76827 | 0.80759 | 0.60569 | 0.08587 | 0.93066 | 0.36814 | 0.78519 | 0.25225 | 0.9384 | 0.80081 | 0.83368 | 0.36966 | 0.56348 | 0.88486 |
neuralnet -addlayer 8 | 0.43541 | 0.26541 | 0.75919 | 0.76102 | 0.53673 | 0.74248 | 0.32383 | 1 | 0.92801 | 0.96 | 0.65385 | 0.94477 | 0.58089 | 0.97465 | 0.47964 | 0.98874 | 0.5875 | 0.64516 | 0.66899 | 0.7 | 0.71257 | 0.64896 | 0.83929 | 0.33458 | 0.51027 | 0.63741 | 0.50889 | 0.78571 | 0.92285 | 0.86263 | 0.95867 | 0.98792 | 0.46956 | 0.51946 | 0.75833 | 0.44695 | 0.4125 | 0.82432 | 0.38542 | 0.65605 | 1 | 0.84586 | 0.97431 | 0.97114 | 0.54 | 0.377 | 0.32502 | 0.93876 | 0.75481 | 0.90219 | 0.58369 | 0.07985 | 0.93868 | 0.35093 | 0.78692 | 0.23499 | 0.94437 | 0.86384 | 0.83576 | 0.34944 | 0.58235 | 0.89278 |
graphcuttransducer 32 | 0.45517 | 0.0020109 | 0.83387 | 0.92205 | 0.54823 | 0.28673 | 0.18751 | 0.92653 | 0.86527 | 0.52 | 0.70559 | 0.9671 | 0.59191 | 0.70035 | 0.099914 | 0.90682 | 0.62011 | 0.58387 | 0.83739 | 0.7008 | 0.75355 | 0.70495 | 0.77143 | 0.50841 | 0.83234 | 0.81429 | 0.82815 | 0.76522 | 0.93505 | 0.82393 | 0.92 | 0.9179 | 0.099914 | 0.61392 | 0.55 | 0.76066 | 0.2875 | 0.72568 | 0.42083 | 0.82619 | 0.99938 | 0.94656 | 0.80801 | 0.97011 | 0.66667 | 0.32503 | 0.90277 | 0.94576 | 0.64423 | 0.59124 | 0.9148 | 0.054247 | 0.8052 | 0.51663 | 0.78601 | 0.56738 | 0.34424 | 0.77772 | 0.95955 | 0.50795 | 0.41153 | |
neuralnet -addlayer 16 | 0.46776 | 0.26124 | 0.75919 | 0.76169 | 0.53805 | 0.74602 | 0.33461 | 1 | 0.9584 | 0.96 | 0.64755 | 0.94621 | 0.55065 | 0.9816 | 0.56717 | 0.98861 | 0.6087 | 0.64516 | 0.66377 | 0.7 | 0.84262 | 0.64766 | 0.85238 | 0.34299 | 0.50892 | 0.60408 | 0.52 | 0.76653 | 0.92285 | 0.8667 | 0.956 | 0.98924 | 0.5697 | 0.57229 | 0.70833 | 0.70545 | 0.45 | 0.80135 | 0.35208 | 0.66232 | 1 | 0.84595 | 0.97454 | 0.97058 | 0.57333 | 0.3941 | 0.39541 | 0.93876 | 0.80481 | 0.91713 | 0.54696 | 0.089268 | 0.94263 | 0.32182 | 0.788 | 0.2591 | 0.94343 | 0.9 | 0.8348 | 0.35843 | 0.58571 | 0.91486 |
decisiontree -random | 0.4907 | 0.19062 | 0.79432 | 0.41372 | 0.43982 | 0.59412 | 0.90612 | 0.7731 | 0.74 | 0.65315 | 0.93763 | 0.61217 | 0.73576 | 0.38849 | 0.82372 | 0.6712 | 0.63226 | 0.72928 | 0.6594 | 0.72842 | 0.66667 | 0.71429 | 0.58411 | 0.70958 | 0.66815 | 0.75238 | 0.93266 | 0.8239 | 0.944 | 0.82954 | 0.38849 | 0.74064 | 0.53333 | 0.68319 | 0.3375 | 0.67297 | 0.42917 | 0.7706 | 0.99572 | 0.91594 | 0.76162 | 0.53778 | 0.30324 | 0.85939 | 0.93462 | 0.65096 | 0.66091 | 0.87072 | 0.30392 | 0.52589 | 0.51272 | 0.78465 | 0.88141 | 0.69172 | 0.59436 | 0.8236 | 0.43571 | 0.7958 | ||||
meanmarginstree | 0.54928 | 0.20105 | 0.7003 | 0.82494 | 0.53584 | 0.67611 | 0.34345 | 0.81633 | 0.80447 | 0.94 | 0.65594 | 0.94477 | 0.56699 | 0.87118 | 0.4751 | 0.93242 | 0.63261 | 0.79355 | 0.62406 | 0.6104 | 0.53497 | 0.67005 | 0.77917 | 0.50374 | 0.57492 | 0.63946 | 0.58074 | 0.70063 | 0.92285 | 0.90312 | 0.93067 | 0.93041 | 0.47153 | 0.61773 | 0.75833 | 0.79446 | 0.4 | 0.7 | 0.62708 | 0.72546 | 0.99958 | 0.94353 | 0.94094 | 0.94992 | 0.54889 | 0.36107 | 0.80658 | 0.93876 | 0.77019 | 0.87878 | 0.71284 | 0.46744 | 0.9106 | 0.51539 | 0.78419 | 0.54113 | 0.93746 | 0.84465 | 0.77268 | 0.68764 | 0.48625 | 0.92871 |
graphcuttransducer 16 | 0.56372 | 0.009959 | 0.83477 | 0.94922 | 0.54867 | 0.34602 | 0.36779 | 0.98027 | 0.86335 | 0.5 | 0.71888 | 0.96653 | 0.60818 | 0.70718 | 0.10638 | 0.93467 | 0.67065 | 0.64516 | 0.85449 | 0.7064 | 0.91585 | 0.71745 | 0.82679 | 0.5729 | 0.82044 | 0.81224 | 0.81852 | 0.76782 | 0.93515 | 0.83475 | 0.96267 | 0.93792 | 0.10638 | 0.61392 | 0.55 | 0.84659 | 0.29375 | 0.80676 | 0.42083 | 0.83353 | 1 | 0.95535 | 0.90412 | 0.97011 | 0.66667 | 0.92338 | 0.95896 | 0.71346 | 0.80557 | 0.91754 | 0.10098 | 0.8121 | 0.51281 | 0.78464 | 0.65721 | 0.92 | 0.60586 | 0.78416 | 0.96292 | 0.52588 | 0.5938 | |
knn 1 -equalweight | 0.60976 | 0.19957 | 0.79624 | 0.97216 | 0.5615 | 0.65929 | 0.6565 | 0.98571 | 0.78208 | 0.82 | 0.68112 | 0.9485 | 0.6064 | 0.79988 | 0.38488 | 0.89186 | 0.69348 | 0.74839 | 0.80493 | 0.6812 | 0.9224 | 0.6987 | 0.80357 | 0.66262 | 0.75378 | 0.77347 | 0.77259 | 0.78715 | 0.92147 | 0.85533 | 0.948 | 0.90094 | 0.38488 | 0.76773 | 0.63333 | 0.93735 | 0.375 | 0.79324 | 0.41042 | 0.80944 | 1 | 0.93031 | 0.77914 | 0.95071 | 0.56 | 0.35749 | 0.94918 | 0.95551 | 0.82404 | 0.90746 | 0.89507 | 0.4083 | 0.73705 | 0.50996 | 0.72595 | 0.6896 | 0.91541 | 0.95636 | 0.7066 | 0.94045 | 0.50418 | 0.86537 |
knn 1 -equalweight -scalefeatures | 0.61194 | 0.19957 | 0.79624 | 0.97216 | 0.5615 | 0.65929 | 0.6565 | 0.98571 | 0.78208 | 0.82 | 0.68112 | 0.9485 | 0.6064 | 0.79988 | 0.38488 | 0.89186 | 0.69348 | 0.74839 | 0.80493 | 0.6812 | 0.9224 | 0.6987 | 0.80536 | 0.66262 | 0.74328 | 0.78435 | 0.77259 | 0.78715 | 0.92147 | 0.85533 | 0.948 | 0.90094 | 0.38488 | 0.79717 | 0.63333 | 0.93735 | 0.375 | 0.79324 | 0.41042 | 0.80944 | 1 | 0.93031 | 0.77914 | 0.95071 | 0.56 | 0.35749 | 0.94918 | 0.95551 | 0.82404 | 0.89575 | 0.89507 | 0.4083 | 0.73705 | 0.50996 | 0.72595 | 0.68534 | 0.91541 | 0.95636 | 0.7066 | 0.94045 | 0.50418 | 0.86537 |
knn 1 | 0.61613 | 0.19957 | 0.79624 | 0.97216 | 0.56327 | 0.65929 | 0.65553 | 0.98571 | 0.78208 | 0.82 | 0.68112 | 0.9485 | 0.6064 | 0.79988 | 0.38488 | 0.89186 | 0.70326 | 0.74839 | 0.80348 | 0.6812 | 0.9224 | 0.6987 | 0.80357 | 0.66262 | 0.75378 | 0.78776 | 0.77259 | 0.78205 | 0.92174 | 0.85533 | 0.948 | 0.90094 | 0.38488 | 0.7085 | 0.63333 | 0.93735 | 0.43125 | 0.79324 | 0.47917 | 0.80944 | 1 | 0.93031 | 0.77914 | 0.95189 | 0.56 | 0.35749 | 0.94918 | 0.95551 | 0.82404 | 0.89575 | 0.89507 | 0.4083 | 0.73705 | 0.50996 | 0.72595 | 0.6896 | 0.91541 | 0.95636 | 0.7066 | 0.94045 | 0.50418 | 0.86537 |
knn 1 -scalefeatures | 0.61893 | 0.19957 | 0.79624 | 0.97216 | 0.56327 | 0.65929 | 0.65553 | 0.98571 | 0.78495 | 0.82 | 0.68112 | 0.9485 | 0.6093 | 0.79988 | 0.38488 | 0.89186 | 0.70326 | 0.74839 | 0.80348 | 0.6812 | 0.9224 | 0.6987 | 0.80357 | 0.66262 | 0.75378 | 0.78776 | 0.77259 | 0.78205 | 0.92174 | 0.84727 | 0.948 | 0.90094 | 0.38488 | 0.7085 | 0.63333 | 0.93735 | 0.43125 | 0.79324 | 0.47917 | 0.80944 | 1 | 0.93031 | 0.77258 | 0.95189 | 0.56 | 0.35749 | 0.94918 | 0.95551 | 0.82404 | 0.89575 | 0.89507 | 0.4083 | 0.73705 | 0.50996 | 0.6896 | 0.91541 | 0.95232 | 0.7066 | 0.94045 | 0.50418 | 0.86537 | |
graphcuttransducer 2 | 0.64562 | 0.15767 | 0.80411 | 0.94788 | 0.58982 | 0.60531 | 0.64959 | 0.97891 | 0.71773 | 0.97 | 0.71678 | 0.9505 | 0.58029 | 0.76123 | 0.24673 | 0.91258 | 0.69891 | 0.74516 | 0.81942 | 0.6924 | 0.93607 | 0.70885 | 0.81012 | 0.68411 | 0.76431 | 0.79252 | 0.77407 | 0.7975 | 0.9263 | 0.86328 | 0.924 | 0.92153 | 0.24673 | 0.74717 | 0.63333 | 0.93269 | 0.4125 | 0.77568 | 0.42083 | 0.81893 | 1 | 0.95577 | 0.83182 | 0.96112 | 0.59111 | 0.35688 | 0.93766 | 0.95467 | 0.81538 | 0.91304 | 0.90467 | 0.32658 | 0.71442 | 0.5047 | 0.75438 | 0.6747 | 0.91862 | 0.96626 | 0.73012 | 0.94719 | 0.52062 | 0.92282 |
bag 8 decisiontree -random end | 0.65775 | 0.22303 | 0.83121 | 0.76437 | 0.55575 | 0.53363 | 0.65276 | 0.97279 | 0.82207 | 0.84 | 0.71119 | 0.95766 | 0.62548 | 0.81042 | 0.48311 | 0.90451 | 0.73533 | 0.6 | 0.82986 | 0.712 | 0.88033 | 0.72266 | 0.80476 | 0.65234 | 0.77757 | 0.79728 | 0.7963 | 0.79219 | 0.95027 | 0.89403 | 0.94 | 0.91546 | 0.48311 | 0.76502 | 0.58333 | 0.84808 | 0.35625 | 0.73649 | 0.56042 | 0.83759 | 0.99983 | 0.93859 | 0.90693 | 0.97121 | 0.58444 | 0.38351 | 0.94372 | 0.95769 | 0.72885 | 0.78654 | 0.92906 | 0.3642 | 0.67755 | 0.49677 | 0.78455 | 0.69007 | 0.92872 | 0.82667 | 0.71712 | 0.9382 | 0.531 | 0.85133 |
graphcuttransducer 8 | 0.65847 | 0.031458 | 0.82923 | 0.96414 | 0.57965 | 0.44779 | 0.47525 | 0.99456 | 0.84798 | 0.81 | 0.73287 | 0.9671 | 0.59945 | 0.74514 | 0.12231 | 0.94656 | 0.70326 | 0.67742 | 0.85101 | 0.716 | 0.94044 | 0.72917 | 0.83512 | 0.6 | 0.81649 | 0.80136 | 0.81704 | 0.78203 | 0.93653 | 0.84102 | 0.956 | 0.9485 | 0.12231 | 0.62771 | 0.60833 | 0.90222 | 0.3 | 0.81351 | 0.42083 | 0.83931 | 1 | 0.96338 | 0.87262 | 0.97003 | 0.66444 | 0.3769 | 0.93463 | 0.96092 | 0.78462 | 0.8776 | 0.91802 | 0.19513 | 0.80307 | 0.5154 | 0.78528 | 0.70236 | 0.92875 | 0.85919 | 0.77924 | 0.95955 | 0.53935 | 0.78227 |
graphcuttransducer 4 | 0.66938 | 0.082883 | 0.81914 | 0.96592 | 0.60354 | 0.58053 | 0.61064 | 0.98435 | 0.82174 | 0.81 | 0.72867 | 0.96138 | 0.58145 | 0.72569 | 0.17199 | 0.94218 | 0.70489 | 0.71935 | 0.83855 | 0.7176 | 0.94863 | 0.74115 | 0.83155 | 0.66075 | 0.81318 | 0.80408 | 0.80148 | 0.79359 | 0.93669 | 0.85357 | 0.94533 | 0.94556 | 0.17199 | 0.73325 | 0.575 | 0.93039 | 0.34375 | 0.80676 | 0.425 | 0.83662 | 1 | 0.96599 | 0.84168 | 0.96853 | 0.65111 | 0.39224 | 0.94545 | 0.95875 | 0.81538 | 0.90103 | 0.91515 | 0.25763 | 0.76439 | 0.50598 | 0.78273 | 0.70402 | 0.92599 | 0.95657 | 0.75892 | 0.95281 | 0.54286 | 0.87122 |
decisiontree | 0.67212 | 0.19449 | 0.78799 | 0.49027 | 0.52655 | 0.64784 | 1 | 0.77632 | 0.92 | 0.66364 | 0.93619 | 0.62025 | 0.89699 | 0.52223 | 0.99118 | 0.69355 | 0.7913 | 0.667 | 0.89071 | 0.75655 | 0.65607 | 0.71684 | 0.73878 | 0.74889 | 0.76502 | 0.96066 | 0.85474 | 0.94533 | 0.99118 | 0.52223 | 0.6867 | 0.63333 | 0.84251 | 0.5125 | 0.72973 | 0.57083 | 0.81067 | 0.9998 | 0.99897 | 0.96644 | 0.93375 | 0.53556 | 0.33809 | 0.95281 | 0.96076 | 0.72019 | 0.77806 | 0.90263 | 0.39247 | 0.89467 | 0.51 | 0.78628 | 0.69598 | 0.93379 | 0.82929 | 0.7394 | 0.89551 | 0.48086 | 0.41757 | |||
knn 7 -equalweight -scalefeatures | 0.67457 | 0.23031 | 0.83042 | 0.94833 | 0.58673 | 0.55575 | 0.5219 | 0.9517 | 0.87808 | 0.58 | 0.72517 | 0.96595 | 0.60351 | 0.85231 | 0.57442 | 0.93204 | 0.69457 | 0.67419 | 0.84986 | 0.722 | 0.93443 | 0.7276 | 0.83571 | 0.61028 | 0.81911 | 0.80204 | 0.81556 | 0.78586 | 0.93722 | 0.82905 | 0.95333 | 0.93548 | 0.57442 | 0.57562 | 0.56667 | 0.9215 | 0.35 | 0.79595 | 0.40417 | 0.83431 | 0.99919 | 0.92886 | 0.934 | 0.96885 | 0.65778 | 0.42592 | 0.92736 | 0.96098 | 0.72981 | 0.86941 | 0.89633 | 0.40489 | 0.79875 | 0.38681 | 0.68463 | 0.92093 | 0.67737 | 0.78968 | 0.94607 | 0.5593 | 0.72678 | |
knn 7 -equalweight | 0.67608 | 0.23031 | 0.83042 | 0.94833 | 0.58673 | 0.55575 | 0.51034 | 0.9517 | 0.87808 | 0.58 | 0.72517 | 0.96595 | 0.60351 | 0.85231 | 0.57442 | 0.93035 | 0.69457 | 0.67419 | 0.83478 | 0.722 | 0.93443 | 0.7276 | 0.83571 | 0.61028 | 0.81911 | 0.80204 | 0.81556 | 0.78586 | 0.93722 | 0.82963 | 0.95333 | 0.93548 | 0.57442 | 0.558 | 0.56667 | 0.9215 | 0.35 | 0.79595 | 0.40417 | 0.83399 | 0.99919 | 0.92704 | 0.934 | 0.96885 | 0.65778 | 0.42592 | 0.92736 | 0.96098 | 0.72981 | 0.86941 | 0.89633 | 0.40489 | 0.79875 | 0.38681 | 0.78119 | 0.68463 | 0.92093 | 0.67737 | 0.7858 | 0.94607 | 0.5593 | 0.72678 |
knn 3 -equalweight -scalefeatures | 0.67782 | 0.20867 | 0.81943 | 0.96058 | 0.60044 | 0.60088 | 0.5376 | 0.97823 | 0.82976 | 0.83 | 0.70699 | 0.96109 | 0.59019 | 0.82141 | 0.39614 | 0.9281 | 0.71957 | 0.74194 | 0.83681 | 0.7062 | 0.93825 | 0.72813 | 0.83631 | 0.63458 | 0.80462 | 0.78571 | 0.81556 | 0.79487 | 0.93526 | 0.84163 | 0.94133 | 0.93579 | 0.39614 | 0.67365 | 0.68333 | 0.92924 | 0.3625 | 0.7973 | 0.40833 | 0.82778 | 1 | 0.93928 | 0.86218 | 0.96703 | 0.59333 | 0.3846 | 0.93558 | 0.95981 | 0.80096 | 0.8896 | 0.89663 | 0.39247 | 0.76107 | 0.39205 | 0.75328 | 0.68794 | 0.92139 | 0.85939 | 0.74784 | 0.94831 | 0.53356 | 0.8002 |
knn 3 -equalweight | 0.67819 | 0.20867 | 0.81943 | 0.96058 | 0.60044 | 0.60088 | 0.54547 | 0.97823 | 0.82976 | 0.83 | 0.70699 | 0.96109 | 0.59019 | 0.82141 | 0.39614 | 0.9276 | 0.70435 | 0.74194 | 0.83681 | 0.7062 | 0.93825 | 0.72813 | 0.83631 | 0.63458 | 0.80462 | 0.7966 | 0.81556 | 0.79487 | 0.93584 | 0.84163 | 0.94133 | 0.93579 | 0.39614 | 0.67365 | 0.68333 | 0.92924 | 0.3625 | 0.80135 | 0.40833 | 0.82778 | 1 | 0.93928 | 0.86218 | 0.59333 | 0.3846 | 0.93558 | 0.95981 | 0.77308 | 0.8896 | 0.89663 | 0.39247 | 0.76107 | 0.4027 | 0.75328 | 0.70189 | 0.92139 | 0.85939 | 0.74784 | 0.94831 | 0.53356 | 0.8002 | |
bag 1 decisiontree 1 meanmarginstree 1 knn 1 1 knn 5 1 neuralnet -addlayer 5 1 discretize naivebayes -ess 0.5 end | 0.67879 | 0.21216 | 0.81198 | 0.902 | 0.56372 | 0.67522 | 0.58534 | 0.96327 | 0.84065 | 0.77 | 0.70769 | 0.94735 | 0.57625 | 0.88287 | 0.49745 | 0.97935 | 0.74022 | 0.70968 | 0.80551 | 0.86066 | 0.71172 | 0.82798 | 0.60561 | 0.75381 | 0.70068 | 0.74963 | 0.68513 | 0.92285 | 0.90597 | 0.92133 | 0.94931 | 0.49532 | 0.6415 | 0.65833 | 0.9136 | 0.4375 | 0.77568 | 0.48333 | 0.80962 | 0.99978 | 0.97639 | 0.95724 | 0.97098 | 0.53333 | 0.40526 | 0.94355 | 0.94231 | 0.78846 | 0.89312 | 0.8366 | 0.44257 | 0.44642 | 0.73614 | 0.67636 | 0.94253 | 0.88949 | 0.79492 | 0.90112 | 0.55283 | 0.85725 | ||
bucket decisiontree meanmarginstree end | 0.68086 | 0.19344 | 0.78797 | 0.79755 | 0.52743 | 0.7 | 0.63029 | 1 | 0.79488 | 0.92 | 0.66503 | 0.94135 | 0.59358 | 0.89178 | 0.52474 | 0.99118 | 0.78152 | 0.75161 | 0.79681 | 0.6754 | 0.89071 | 0.68047 | 0.79107 | 0.64299 | 0.72276 | 0.71429 | 0.73852 | 0.77677 | 0.96193 | 0.90597 | 0.92933 | 0.99118 | 0.52471 | 0.675 | 0.8457 | 0.4375 | 0.73784 | 0.61667 | 0.81037 | 0.99985 | 0.99842 | 0.96826 | 0.94819 | 0.56 | 0.34686 | 0.95333 | 0.96326 | 0.75096 | 0.87468 | 0.90545 | 0.48881 | 0.78546 | 0.70189 | 0.93839 | 0.85051 | 0.77352 | 0.90225 | 0.48437 | 0.90898 | |||
categorize knn 3 | 0.6878 | 0.20239 | 0.81089 | 0.95947 | 0.58407 | 0.58407 | 0.62813 | 0.98435 | 0.82176 | 0.86 | 0.67203 | 0.96137 | 0.59888 | 0.79606 | 0.62986 | 0.92065 | 0.68967 | 0.74194 | 0.83014 | 0.7018 | 0.93497 | 0.71875 | 0.83036 | 0.66262 | 0.77426 | 0.78435 | 0.81037 | 0.79491 | 0.93165 | 0.83191 | 0.94 | 0.91471 | 0.63067 | 0.65948 | 0.55 | 0.39375 | 0.77432 | 0.47917 | 0.82879 | 0.99985 | 0.97417 | 0.88878 | 0.61556 | 0.36399 | 0.94684 | 0.95832 | 0.78558 | 0.90981 | 0.40978 | 0.74426 | 0.53637 | 0.68865 | 0.92048 | 0.9396 | 0.74824 | 0.95169 | 0.52588 | 0.9189 | ||||
knn 5 -equalweight -scalefeatures | 0.68903 | 0.21934 | 0.82645 | 0.95256 | 0.60133 | 0.59027 | 0.53354 | 0.96803 | 0.8592 | 0.83 | 0.72168 | 0.96452 | 0.59362 | 0.84595 | 0.51781 | 0.93204 | 0.69837 | 0.71613 | 0.84261 | 0.7168 | 0.93825 | 0.73542 | 0.84345 | 0.62523 | 0.8145 | 0.79252 | 0.82444 | 0.78843 | 0.9368 | 0.82964 | 0.95067 | 0.93705 | 0.51781 | 0.59975 | 0.60833 | 0.92591 | 0.35 | 0.79595 | 0.40625 | 0.83198 | 0.99961 | 0.93604 | 0.91651 | 0.96822 | 0.64667 | 0.40819 | 0.92823 | 0.96156 | 0.73846 | 0.88756 | 0.89546 | 0.40677 | 0.77486 | 0.39461 | 0.77919 | 0.68345 | 0.75879 | 0.77228 | 0.95056 | 0.5527 | 0.77051 | |
knn 5 -equalweight | 0.69306 | 0.21934 | 0.82645 | 0.95189 | 0.60133 | 0.59027 | 0.53354 | 0.96803 | 0.8592 | 0.83 | 0.72168 | 0.96452 | 0.59362 | 0.84595 | 0.51781 | 0.93204 | 0.69837 | 0.71613 | 0.84261 | 0.7168 | 0.93825 | 0.73542 | 0.84345 | 0.62523 | 0.8145 | 0.79252 | 0.81778 | 0.78843 | 0.9368 | 0.82962 | 0.95067 | 0.93705 | 0.51781 | 0.59975 | 0.60833 | 0.92591 | 0.35 | 0.8 | 0.40625 | 0.83198 | 0.99961 | 0.93604 | 0.91651 | 0.64444 | 0.40819 | 0.92996 | 0.96156 | 0.73846 | 0.88756 | 0.89546 | 0.40677 | 0.77486 | 0.4054 | 0.77919 | 0.68345 | 0.92047 | 0.75879 | 0.77228 | 0.95056 | 0.5527 | 0.77051 | |
knn 3 | 0.71527 | 0.20239 | 0.8116 | 0.96771 | 0.59336 | 0.66991 | 0.64093 | 0.98367 | 0.82176 | 0.87 | 0.71608 | 0.96137 | 0.59888 | 0.82141 | 0.39634 | 0.93016 | 0.70707 | 0.74194 | 0.8313 | 0.7064 | 0.93934 | 0.71875 | 0.83036 | 0.65794 | 0.7901 | 0.79524 | 0.81037 | 0.80651 | 0.93293 | 0.84675 | 0.948 | 0.93698 | 0.40347 | 0.65234 | 0.7 | 0.93906 | 0.39375 | 0.81757 | 0.47917 | 0.82879 | 1 | 0.94586 | 0.86222 | 0.96743 | 0.58889 | 0.37635 | 0.94771 | 0.96013 | 0.78558 | 0.906 | 0.9055 | 0.43128 | 0.77524 | 0.50332 | 0.75328 | 0.70236 | 0.91955 | 0.94202 | 0.74824 | 0.95169 | 0.53235 | 0.85953 |
knn 3 -scalefeatures | 0.71543 | 0.20239 | 0.8116 | 0.96771 | 0.59336 | 0.66991 | 0.64093 | 0.98367 | 0.81951 | 0.87 | 0.71608 | 0.96137 | 0.60173 | 0.82141 | 0.39634 | 0.93016 | 0.70707 | 0.74194 | 0.8313 | 0.7064 | 0.93934 | 0.71875 | 0.83036 | 0.65794 | 0.7901 | 0.79524 | 0.81037 | 0.80651 | 0.93293 | 0.84675 | 0.948 | 0.93698 | 0.39634 | 0.65234 | 0.7 | 0.93906 | 0.39375 | 0.81757 | 0.47917 | 0.82879 | 1 | 0.94586 | 0.86222 | 0.96743 | 0.58889 | 0.37635 | 0.94771 | 0.96013 | 0.78558 | 0.90542 | 0.9055 | 0.43128 | 0.77524 | 0.50465 | 0.75328 | 0.70236 | 0.91955 | 0.94202 | 0.74824 | 0.95169 | 0.53235 | 0.85953 |
bag 8 decisiontree end | 0.75103 | 0.21618 | 0.80963 | 0.76169 | 0.55973 | 0.5292 | 0.62252 | 1 | 0.7923 | 0.82 | 0.67133 | 0.95336 | 0.67594 | 0.88843 | 0.51401 | 0.98798 | 0.8337 | 0.69677 | 0.81478 | 0.7182 | 0.91202 | 0.7375 | 0.81726 | 0.68318 | 0.75312 | 0.78299 | 0.78667 | 0.78843 | 0.96585 | 0.91228 | 0.944 | 0.98798 | 0.51401 | 0.81071 | 0.53333 | 0.89023 | 0.38125 | 0.77297 | 0.65208 | 0.85902 | 0.99993 | 0.99836 | 0.96715 | 0.96995 | 0.55556 | 0.40061 | 0.96649 | 0.96983 | 0.76731 | 0.78505 | 0.93428 | 0.45577 | 0.91925 | 0.51663 | 0.78619 | 0.71868 | 0.95265 | 0.84141 | 0.80348 | 0.93708 | 0.55943 | 0.41 |
knn 5 | 0.75235 | 0.21489 | 0.81781 | 0.96682 | 0.60841 | 0.66726 | 0.64966 | 0.98299 | 0.84832 | 0.89 | 0.72098 | 0.96538 | 0.6081 | 0.84861 | 0.51874 | 0.93705 | 0.70217 | 0.71613 | 0.83449 | 0.7176 | 0.94098 | 0.72995 | 0.84405 | 0.65607 | 0.80526 | 0.7966 | 0.81556 | 0.81039 | 0.936 | 0.83477 | 0.952 | 0.94161 | 0.51874 | 0.66638 | 0.64167 | 0.93922 | 0.36875 | 0.80541 | 0.47917 | 0.83498 | 0.99998 | 0.94768 | 0.91704 | 0.96869 | 0.62444 | 0.4041 | 0.94537 | 0.96209 | 0.775 | 0.90892 | 0.90898 | 0.43201 | 0.80182 | 0.50333 | 0.78001 | 0.69362 | 0.92185 | 0.93636 | 0.77272 | 0.95506 | 0.55377 | 0.84365 |
knn 5 -scalefeatures | 0.75808 | 0.2124 | 0.81781 | 0.9657 | 0.60841 | 0.66726 | 0.64966 | 0.98299 | 0.84832 | 0.89 | 0.72098 | 0.96538 | 0.6081 | 0.84861 | 0.51874 | 0.93623 | 0.70217 | 0.71613 | 0.83449 | 0.7176 | 0.94098 | 0.72995 | 0.84405 | 0.65607 | 0.80526 | 0.7966 | 0.81556 | 0.81039 | 0.936 | 0.83477 | 0.952 | 0.94161 | 0.51874 | 0.66638 | 0.69167 | 0.93922 | 0.36875 | 0.80541 | 0.47917 | 0.83498 | 1 | 0.94829 | 0.91704 | 0.62444 | 0.4041 | 0.94537 | 0.96209 | 0.775 | 0.90102 | 0.90898 | 0.43201 | 0.80182 | 0.50333 | 0.78001 | 0.69385 | 0.92185 | 0.93636 | 0.77272 | 0.95506 | 0.55377 | 0.84365 | |
knn 7 -scalefeatures | 0.76471 | 0.22145 | 0.82214 | 0.9657 | 0.60398 | 0.64779 | 0.64483 | 0.97891 | 0.8704 | 0.86 | 0.72308 | 0.96624 | 0.61739 | 0.86204 | 0.57918 | 0.94005 | 0.69783 | 0.68387 | 0.84667 | 0.7248 | 0.94044 | 0.72656 | 0.84821 | 0.65607 | 0.8178 | 0.80204 | 0.81704 | 0.81167 | 0.93802 | 0.83133 | 0.95333 | 0.94412 | 0.57918 | 0.66281 | 0.625 | 0.93715 | 0.35625 | 0.80811 | 0.47917 | 0.83858 | 0.99995 | 0.94726 | 0.93698 | 0.96916 | 0.64667 | 0.41943 | 0.94511 | 0.96098 | 0.76923 | 0.89663 | 0.91272 | 0.42825 | 0.82063 | 0.50739 | 0.78201 | 0.69385 | 0.92185 | 0.93273 | 0.79012 | 0.95281 | 0.56887 | 0.83757 |
knn 7 | 0.76896 | 0.22145 | 0.82214 | 0.9657 | 0.60398 | 0.64779 | 0.64483 | 0.97891 | 0.8704 | 0.86 | 0.72308 | 0.96624 | 0.61739 | 0.86204 | 0.57918 | 0.94005 | 0.69783 | 0.68387 | 0.83333 | 0.7248 | 0.94044 | 0.72917 | 0.84821 | 0.65607 | 0.8178 | 0.80204 | 0.81704 | 0.81167 | 0.93802 | 0.83133 | 0.95333 | 0.94412 | 0.57918 | 0.68805 | 0.63333 | 0.93715 | 0.35625 | 0.80811 | 0.47917 | 0.83858 | 0.99995 | 0.94726 | 0.93435 | 0.96916 | 0.64667 | 0.41943 | 0.94511 | 0.96235 | 0.79327 | 0.89663 | 0.91272 | 0.42825 | 0.82063 | 0.50739 | 0.78201 | 0.69385 | 0.92185 | 0.93273 | 0.78616 | 0.95281 | 0.56887 | 0.83757 |
calibrator bag 32 decisiontree end | 0.77416 | 0.17678 | 0.81045 | 0.55398 | 0.63009 | 0.62725 | 1 | 0.80991 | 0.84 | 0.66084 | 0.95393 | 0.68578 | 0.8963 | 0.44224 | 0.98949 | 0.83315 | 0.76452 | 0.82087 | 0.7084 | 0.91038 | 0.75443 | 0.82917 | 0.71121 | 0.77165 | 0.79932 | 0.80963 | 0.80263 | 0.96866 | 0.91683 | 0.948 | 0.98949 | 0.44224 | 0.81761 | 0.65833 | 0.26374 | 0.45625 | 0.76081 | 0.64792 | 0.87093 | 1 | 0.99921 | 0.97059 | 0.96751 | 0.58222 | 0.35451 | 0.97238 | 0.9693 | 0.77019 | 0.59502 | 0.9428 | 0.28248 | 0.92596 | 0.51532 | 0.78792 | 0.73522 | 0.95358 | 0.88222 | 0.82568 | 0.96404 | 0.5504 | 0.42161 | |
bag 16 decisiontree end | 0.78181 | 0.22791 | 0.81168 | 0.76169 | 0.56106 | 0.5531 | 0.65286 | 1 | 0.80865 | 0.86 | 0.67203 | 0.95508 | 0.6771 | 0.89664 | 0.52541 | 0.99161 | 0.8288 | 0.70968 | 0.8258 | 0.7124 | 0.91202 | 0.74922 | 0.83333 | 0.71402 | 0.75965 | 0.78639 | 0.80296 | 0.80123 | 0.96771 | 0.91453 | 0.944 | 0.99161 | 0.52541 | 0.84224 | 0.58333 | 0.90784 | 0.36875 | 0.75946 | 0.68333 | 0.86717 | 0.9998 | 0.99909 | 0.97157 | 0.97058 | 0.59111 | 0.39585 | 0.97212 | 0.96988 | 0.78173 | 0.80468 | 0.93967 | 0.47536 | 0.92533 | 0.50072 | 0.78292 | 0.7305 | 0.95309 | 0.86889 | 0.82096 | 0.93708 | 0.57628 | 0.41835 |
bag 16 decisiontree -random end | 0.79074 | 0.23074 | 0.83765 | 0.76169 | 0.56947 | 0.57699 | 0.68098 | 0.9898 | 0.82752 | 0.82 | 0.70909 | 0.96538 | 0.66379 | 0.8147 | 0.54534 | 0.93648 | 0.76087 | 0.6871 | 0.83797 | 0.7168 | 0.92295 | 0.73854 | 0.82917 | 0.69813 | 0.79337 | 0.79456 | 0.8163 | 0.83092 | 0.95429 | 0.92251 | 0.94 | 0.93592 | 0.54534 | 0.8814 | 0.675 | 0.89209 | 0.44375 | 0.75405 | 0.63125 | 0.85474 | 1 | 0.94674 | 0.93648 | 0.97129 | 0.61556 | 0.40003 | 0.95333 | 0.96007 | 0.74808 | 0.84159 | 0.94249 | 0.42526 | 0.7353 | 0.51137 | 0.78646 | 0.71489 | 0.9338 | 0.90081 | 0.76164 | 0.95618 | 0.56307 | 0.89729 |
bag 8 bucket decisiontree meanmarginstree end end | 0.79933 | 0.22456 | 0.80939 | 0.83207 | 0.69912 | 1 | 0.84095 | 0.76 | 0.7035 | 0.96281 | 0.63543 | 0.89595 | 0.53142 | 0.99055 | 0.76452 | 0.82551 | 0.89672 | 0.73438 | 0.82024 | 0.69907 | 0.74651 | 0.79456 | 0.79037 | 0.79224 | 0.96617 | 0.92251 | 0.952 | 0.99055 | 0.53298 | 0.7649 | 0.68333 | 0.89141 | 0.40625 | 0.74595 | 0.65417 | 0.8603 | 0.9998 | 0.99836 | 0.96577 | 0.96916 | 0.57778 | 0.39829 | 0.96926 | 0.96882 | 0.77115 | 0.89665 | 0.93727 | 0.52201 | 0.92934 | 0.47158 | 0.78419 | 0.72506 | 0.95035 | 0.88424 | 0.80924 | 0.93708 | 0.55202 | 0.87718 | ||||
bucket decisiontree meanmarginstree knn 1 knn 5 neuralnet -addlayer 5 discretize naivebayes -ess 0.5 end | 0.8082 | 0.20919 | 0.8181 | 0.96726 | 0.60752 | 0.65221 | 0.6567 | 1 | 0.88609 | 0.83 | 0.6972 | 0.96452 | 0.60177 | 0.9287 | 0.51945 | 0.9893 | 0.72772 | 0.81768 | 0.724 | 0.92623 | 0.72266 | 0.83274 | 0.6729 | 0.80855 | 0.78707 | 0.80148 | 0.79229 | 0.9622 | 0.89172 | 0.944 | 0.98867 | 0.52084 | 0.68333 | 0.93713 | 0.41875 | 0.78649 | 0.8355 | 0.99983 | 0.99964 | 0.96403 | 0.89779 | 0.49111 | 0.38045 | 0.94762 | 0.96156 | 0.81827 | 0.89577 | 0.91037 | 0.4712 | 0.91574 | 0.49546 | 0.78501 | 0.69645 | 0.94347 | 0.94626 | 0.75432 | 0.94719 | 0.55997 | 0.89333 | |||
bag 64 decisiontree -random end | 0.81862 | 0.24328 | 0.84411 | 0.76169 | 0.56239 | 0.57876 | 0.71524 | 0.99184 | 0.85344 | 0.87 | 0.71748 | 0.96767 | 0.69569 | 0.84201 | 0.61984 | 0.95945 | 0.78967 | 0.64839 | 0.85536 | 0.7206 | 0.95738 | 0.74922 | 0.84107 | 0.73271 | 0.82111 | 0.81156 | 0.81778 | 0.83365 | 0.95583 | 0.91851 | 0.948 | 0.9587 | 0.61984 | 0.89076 | 0.63333 | 0.93096 | 0.39375 | 0.8 | 0.63125 | 0.86685 | 1 | 0.94856 | 0.95829 | 0.97121 | 0.65778 | 0.44544 | 0.96667 | 0.96278 | 0.7875 | 0.87174 | 0.94871 | 0.44216 | 0.76533 | 0.48346 | 0.78537 | 0.72861 | 0.9476 | 0.93212 | 0.81632 | 0.97079 | 0.58827 | 0.90302 |
bag 32 decisiontree -random end | 0.82017 | 0.24008 | 0.84013 | 0.76169 | 0.56681 | 0.58673 | 0.70247 | 0.98231 | 0.84096 | 0.83 | 0.70909 | 0.96968 | 0.68062 | 0.83935 | 0.58767 | 0.95038 | 0.77989 | 0.61935 | 0.84986 | 0.7238 | 0.94426 | 0.74141 | 0.83274 | 0.73364 | 0.82375 | 0.81633 | 0.81778 | 0.83228 | 0.95435 | 0.92478 | 0.94133 | 0.95225 | 0.58767 | 0.85567 | 0.66667 | 0.91702 | 0.4125 | 0.76622 | 0.65417 | 0.8613 | 1 | 0.94829 | 0.95157 | 0.97129 | 0.61778 | 0.4159 | 0.96346 | 0.96246 | 0.77308 | 0.85418 | 0.94662 | 0.43918 | 0.76157 | 0.53775 | 0.78555 | 0.73215 | 0.93883 | 0.90788 | 0.79648 | 0.96067 | 0.5845 | 0.91278 |
bag 32 decisiontree end | 0.82846 | 0.23443 | 0.81102 | 0.76169 | 0.56549 | 0.59646 | 0.65072 | 1 | 0.80928 | 1 | 0.66573 | 0.96108 | 0.69276 | 0.89965 | 0.53518 | 0.99018 | 0.84457 | 0.77419 | 0.82058 | 0.7074 | 0.90546 | 0.75417 | 0.83274 | 0.73832 | 0.76695 | 0.8034 | 0.79852 | 0.80395 | 0.96972 | 0.9077 | 0.95333 | 0.99018 | 0.53518 | 0.81478 | 0.69167 | 0.9144 | 0.44375 | 0.7473 | 0.71458 | 0.87137 | 0.99966 | 0.99912 | 0.97168 | 0.9709 | 0.56 | 0.4195 | 0.97108 | 0.97147 | 0.79519 | 0.81466 | 0.9414 | 0.50248 | 0.92752 | 0.49811 | 0.78564 | 0.73806 | 0.95678 | 0.88545 | 0.83036 | 0.9427 | 0.57345 | 0.41208 |
bag 64 decisiontree end | 0.83061 | 0.2317 | 0.81158 | 0.76169 | 0.56283 | 0.63274 | 0.63317 | 1 | 0.80897 | 0.9 | 0.65874 | 0.96309 | 0.68578 | 0.90093 | 0.53566 | 0.9913 | 0.84946 | 0.75806 | 0.82435 | 0.7188 | 0.91475 | 0.75104 | 0.81964 | 0.72336 | 0.76367 | 0.79932 | 0.80148 | 0.80784 | 0.96877 | 0.92138 | 0.94533 | 0.9913 | 0.53566 | 0.81379 | 0.70833 | 0.91766 | 0.3875 | 0.77838 | 0.73125 | 0.87321 | 0.99975 | 0.99912 | 0.97241 | 0.96995 | 0.59111 | 0.41652 | 0.97524 | 0.97121 | 0.8032 | 0.94479 | 0.51226 | 0.9284 | 0.49668 | 0.78746 | 0.7435 | 0.95723 | 0.88667 | 0.83284 | 0.94944 | 0.57224 | 0.41361 | |
bag 32 bucket decisiontree meanmarginstree end end | 0.83196 | 0.23419 | 0.81252 | 0.84833 | 0.56726 | 0.71681 | 0.62733 | 1 | 0.86624 | 0.92 | 0.67902 | 0.96052 | 0.68001 | 0.90312 | 0.55715 | 0.9918 | 0.84837 | 0.7108 | 0.91585 | 0.75417 | 0.83929 | 0.69533 | 0.76769 | 0.7932 | 0.81704 | 0.81552 | 0.9684 | 0.92991 | 0.94667 | 0.9918 | 0.55047 | 0.81047 | 0.7 | 0.91485 | 0.41875 | 0.87027 | 0.99993 | 0.99903 | 0.97059 | 0.9694 | 0.62667 | 0.42832 | 0.9716 | 0.97068 | 0.82885 | 0.91655 | 0.9424 | 0.56273 | 0.93436 | 0.46758 | 0.78519 | 0.74303 | 0.95263 | 0.90747 | 0.82612 | 0.95169 | ||||||
bag 64 bucket decisiontree meanmarginstree end end | 0.85193 | 0.23347 | 0.81207 | 0.83853 | 0.57389 | 0.74248 | 0.61847 | 1 | 0.86848 | 0.88 | 0.6965 | 0.96166 | 0.68349 | 0.90787 | 0.55777 | 0.99174 | 0.8129 | 0.82087 | 0.7122 | 0.90273 | 0.74661 | 0.85 | 0.73271 | 0.76169 | 0.79864 | 0.80593 | 0.79759 | 0.96946 | 0.9305 | 0.956 | 0.99174 | 0.55939 | 0.75 | 0.91663 | 0.425 | 0.77432 | 0.7375 | 0.87262 | 0.99998 | 0.99912 | 0.97224 | 0.97035 | 0.62222 | 0.40595 | 0.97377 | 0.971 | 0.83846 | 0.91303 | 0.94406 | 0.93843 | 0.48344 | 0.78764 | 0.75035 | 0.95678 | 0.91455 | 0.58666 | 0.92682 | |||||
bag 16 bucket decisiontree meanmarginstree end end | 0.8571 | 0.81108 | 0.84477 | 0.70354 | 0.62825 | 1 | 0.84704 | 0.87 | 0.6965 | 0.95937 | 0.66208 | 0.90197 | 0.54232 | 0.98955 | 0.83315 | 0.8129 | 0.82609 | 0.709 | 0.89617 | 0.76198 | 0.81667 | 0.71776 | 0.76175 | 0.79592 | 0.8037 | 0.96845 | 0.93107 | 0.94933 | 0.98955 | 0.54359 | 0.85616 | 0.71667 | 0.90515 | 0.44375 | 0.73784 | 0.67708 | 0.86562 | 0.99973 | 0.99891 | 0.96937 | 0.96774 | 0.59778 | 0.42006 | 0.97048 | 0.9701 | 0.81731 | 0.90894 | 0.93897 | 0.54841 | 0.93304 | 0.47835 | 0.78664 | 0.95263 | 0.90545 | 0.81928 | 0.94944 | 0.58059 | 0.89075 |