在这里我们展示如何使用命令行来完成数据与模型的读取及保存, 以及使用命令行来输入参数进行推荐计算.
| Usage: librec <command> [options]... |
| commands: |
| rec run recommender |
| data load data |
| global options: |
| --help display this help text |
| --exec run Recommender |
| --version show Librec version info |
| job options: |
| -conf <file> path to config file |
| -D, -jobconf <prop> set configuration items (key=value) |
| -libjars add entend jar files to classpath |
./librec rec -exec -D rec.recommender.class=globalaverage -conf ../core/src/main/resources/rec/baseline/globalaverage-test.properties -libjars ../lib/log4j-1.2.17.jarrec/data 为指定程序进行推荐算法/数据读取功能.
-exec 为执行推荐算法.在2.0版本中为保留选项
-D | -jobconf [options] 为加载相关配置
-conf [path/to/properties] 加载配置文件
-libjars 为加载其他路径下的jar包到classpath中, 其中lib下的jar包自动加载, 当前脚本为示例
LibRec中一个程序的配置文件分别保存在core/librec.properties和各自算法的独立配置文件内.其中librec.properties 推荐保存的配置为数据的读取分割以及评估. 示例配置如下所示
| # set data directoy |
| dfs.data.dir=../data |
| # set result directory |
| # recommender result will output in this folder |
| dfs.result.dir=../result |
| # not implement in this version |
| # instead of printing logs in console |
| dfs.log.dir=../log |
| data.input.path=filmtrust |
| data.column.format=UIR |
| data.model.splitter=ratio |
| data.model.format=text |
| data.splitter.ratio=rating |
| # splitter, reference to basics.md |
| data.splitter.ratio=0.8 |
| data.splitter.cv.number=5 |
| rec.parallel.support=true |
| # setting evaluation, reference to basics.md |
| rec.eval.enable=true |
| rec.random.seed=1 |
