| # Licensed to the Apache Software Foundation (ASF) under one or more | |
| # contributor license agreements. See the NOTICE file distributed with | |
| # this work for additional information regarding copyright ownership. | |
| # The ASF licenses this file to You under the Apache License, Version 2.0 | |
| # (the "License"); you may not use this file except in compliance with | |
| # the License. You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| # Sample machine learning properties file | |
| Algorithm=MAXENT_QN | |
| Iterations=100 | |
| Cutoff=0 | |
| # Number of threads | |
| Threads=1 | |
| # Costs for L1- and L2-regularization. These parameters must be larger or | |
| # equal to zero. The higher they are, the more penalty will be imposed to | |
| # avoid overfitting. The parameters can be set as follows: | |
| # if L1Cost = 0 and L2Cost = 0, no regularization will be used, | |
| # if L1Cost > 0 and L2Cost = 0, L1 will be used, | |
| # if L1Cost = 0 and L2Cost > 0, L2 will be used, | |
| # if both paramters are set to be larger than 0, Elastic Net | |
| # (i.e. L1 and L2 combined) will be used. | |
| L1Cost=0.1 | |
| L2Cost=0.1 | |
| # Number of Hessian updates to store | |
| NumOfUpdates=15 | |
| # Maximum number of objective function's evaluations | |
| MaxFctEval=30000 |