From 985a7a0a18f763ceae020cef2fbf0db3da17776d Mon Sep 17 00:00:00 2001 From: Andreas Maunz Date: Tue, 31 Jan 2012 08:48:08 +0100 Subject: Adjusted tests to new parameters (see http://goo.gl/lXJBS) --- README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index e854ac3..e979ff6 100644 --- a/README.md +++ b/README.md @@ -35,19 +35,19 @@ REST operations [feature_generation_uri], [prediction_algorithm], [feature_dataset_uri], - [propositionalized=false], [pc_type=null], - [nr_hits=false (class.), true (regr.)], - [min_sim=0.3 (nominal), 0.6 (numeric features)] + [nr_hits=false (class. using wt. maj. vote), true (else)], + [min_sim=0.3 (nominal), 0.4 (numeric features)] + [min_train_performance=0.1] Synopsis -------- -- prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification), "local\_svm\_classification", "local\_svm\_regression (default for regression)", "local\_mlr\_prop". "weighted\_majority\_vote" is not applicable for regression. "local\_mlr\_prop" is not applicable for classification. -- propositionalized: One of "true", "false". Not appplicable when prediction\_algorithm="weighted\_majority\_vote". +- prediction\_algorithm: One of "weighted\_majority\_vote" (default for classification), "local\_svm\_classification", "local\_svm\_regression" (default for regression). "weighted\_majority\_vote" is not applicable for regression. - pc_type: Mandatory for feature dataset, one of [geometrical, topological, electronic, constitutional, hybrid, cpsa]. -- nr_hits: Whether for instantiated models (local\_svm\_kernel = "propositionalized" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="local\_mlr\_prop") nominal features should be instantiated with their occurrence counts in the instances. For non-instantiated models (local\_svm\_kernel = "weighted\_tanimoto" for prediction_algorithm="local\_svm\_classification" or "local\_svm\_regression", or for prediction_algorithm="weighted\_majority\_vote") the neighbor-to-neighbor and neighbor-to-query similarity also integrates these counts, when the parameter is set. One of "true", "false". -- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1]. +- nr_hits: Whether nominal features should be instantiated with their occurrence counts in the instances. One of "true", "false". +- min_sim: The minimum similarity threshold for neighbors. Numeric value in [0,1]. +- min_train_performance. The minimum training performance for "local\_svm\_classification" (Accuracy) and "local\_svm\_regression" (R-squared). Numeric value in [0,1]. See http://www.maunz.de/wordpress/opentox/2011/lazar-models-and-how-to-trigger-them for a graphical overview. -- cgit v1.2.3