weka.MultiSearch_LogitBoost_REPTree
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Uploaded 13-06-2016 by
Jan van Rijn
Weka_3.7.13
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Weka implementation of MultiSearch
Components
Parameters
| -do-not-check-capabilities | If set, classifier capabilities are not checked before classifier is built
(use with caution). | |
| C | Do not try to eliminate colinear attributes. | |
| E | Determines the parameter used for evaluation:
CC = Correlation coefficient
MCC = Matthews correlation coefficient
RMSE = Root mean squared error
RRSE = Root relative squared error
MAE = Mean absolute error
RAE = Root absolute error
COMB = Combined = (1-abs(CC)) + RRSE + RAE
ACC = Accuracy
KAP = Kappa
PREC = Precision (per class)
WPREC = Weighted precision
REC = Recall (per class)
WREC = Weighted recall
AUC = Area under ROC (per class)
WAUC = Weighted area under ROC
PRC = Area under PRC (per class)
WPRC = Weighted area under PRC
FM = F-Measure (per class)
WFM = Weighted F-Measure
TPR = True positive rate (per class)
TNR = True negative rate (per class)
FPR = False positive rate (per class)
FNR = False negative rate (per class)
(default: CC) | default: CC |
| R | Set ridge parameter (default 1.0e-8). | |
| S | Random number seed.
(default 1) | default: 1 |
| W | Full name of base classifier.
(default: weka.classifiers.functions.LinearRegression) | default: weka.classifiers.meta.LogitBoost |
| additional-stats | Output additional statistics. | |
| algorithm | A search algorithm. | default: weka.classifiers.meta.multisearch.DefaultSearch -sample-size 100.0 -initial-folds 2 -subsequent-folds 10 -initial-test-set . -subsequent-test-set . -num-slots 1 -num-slots 1 |
| class-label | The class label index to retrieve the metric for (if applicable). | default: 1 |
| log-file | The log file to log the messages to.
(default: none) | default: /home/rijnjnvan/apps/weka-3-7-13 |
| minimal | Conserve memory, don't keep dataset header and means/stdevs.
Model cannot be printed out if this option is enabled. (default: keep data) | |
| num-decimal-places | The number of decimal places for the output of numbers in the model (default 2). | |
| output-debug-info | If set, classifier is run in debug mode and
may output additional info to the console | |
| search | A property search setup. | |
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