我需要按特征创建分类器,我有 15M 行数据,例如:
{
"app_entertainment" : 1,
"app_widgets" : 2,
"arcade" : 8,
"books_and_reference" : 2,
"comics" : 0,
"brain" : 20,
"business" : 0,
"cards" : 5,
"casual" : 1,
"communication" : 4,
"education" : 0,
"finance" : 1,
"game_wallpaper" : 0,
"game_widgets" : 0,
"health_fitness" : 0,
"libraries_demo" : 0,
"racing" : 1,
"lifestyle" : 1,
"media_video" : 0,
"medical" : 0,
"music_and_audio" : 7,
"news_magazines" : 2,
"personalization" : 1,
"photography" : 0,
"productivity" : 4,
"shopping" : 1,
"social" : 1,
"sports_apps" : 1,
"sports_games" : 7,
"tools" : 15,
"transportation" : 2,
"travel_and_local" : 8,
"weather" : 3,
"app_wallpaper" : 0,
"entertainment" : 0,
"health_and_fitness" : 0,
"libraries_and_demo" : 0,
"media_and_video" : 0,
"news_and_magazines" : 0,
"sports" : 0
}
同样对于这样的每个数据集,我都知道它的真假,布尔值是具有此数据集的用户是否点击了广告。
我如何使用 mahout 训练分类器以及训练后如何分类?
我在网上找到的所有内容都非常抽象,关于如何通过 java 进行操作的示例并不多