ADD:demo for win

config/model/ffm.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 data {
     train {

config/model/fm.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 data {
     train {

config/model/gbdt.conf

@@ -1,6 +1,6 @@
 # local filesystem : "file:///",
 # hdfs filesystem : "hdfs://host"
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 # "gradient_boosting"(default), "random_forest"

config/model/gbhmlr.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

config/model/gbhsdt.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

config/model/gbmlr.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

config/model/gbsdt.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

config/model/linear.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

config/model/multiclass_linear.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

demo/gbdt/regression_l2/local_gbdt.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

demo/gbsdt/binary_classification/gbsdt.conf

@@ -1,4 +1,4 @@
-fs_scheme : "file:///",
+fs_scheme : "local",
 verbose : false,
 
 data {

demo/linear/binary_classification/linear.conf

@@ -51,7 +51,7 @@ feature {
 
 
 model {
-    data_path : "demo/linear/regression/lr.model",
+    data_path : "demo/linear/binary_classification/lr.model",
     delim : ",",
     need_dict : false,
     dict_path : "",

demo/linear/regression/linear.conf

@@ -51,7 +51,7 @@ feature {
 
 
 model {
-    data_path : "demo/linear/binary_classification/l2.model",
+    data_path : "demo/linear/regression/l2.model",
     delim : ",",
     need_dict : false,
     dict_path : "",

demo/win/ffm/binary_classification/ffm.conf

@@ -0,0 +1,139 @@
+fs_scheme : "local",
+verbose : false,
+data {
+    train {
+        data_path : "demo/data/ytklearn/agaricus.train.ytklearn",
+        max_error_tol : 0
+    },
+
+    test {
+        data_path : "demo/data/ytklearn/agaricus.test.ytklearn",
+        max_error_tol : 0
+    },
+
+    delim {
+        x_delim : "###",
+        y_delim : ",",
+        features_delim : ",",
+        feature_name_val_delim : ":",
+        field_delim : "@"
+    },
+
+    // ["[email protected]","[email protected]",...]
+    y_sampling : [],
+    assigned : false,
+    unassigned_mode : "lines_avg" // "files_avg"
+},
+
+feature {
+    feature_hash {
+        need_feature_hash : false,
+        bucket_size : 1000000,
+        seed : 39916801,
+        feature_prefix : "hash_"
+    },
+
+    transform {
+        switch_on : false,
+        // "standardization", "scale_range"
+        mode : "standardization",
+        scale_range {
+            min : -1,
+            max : 1
+        },
+
+        include_features : [],
+        exclude_features : []
+    },
+
+    filter_threshold : 0
+},
+
+model {
+    data_path : "demo/win/ffm/binary_classification/ffm.model",
+    delim : ",",
+    need_dict : false,
+    dict_path : "",
+    field_dict_path : "demo/win/ffm/binary_classification/field.dict",
+    dump_freq : 50,
+    need_bias : true,
+    bias_feature_name : "_bias_",
+    continue_train : false
+},
+
+loss {
+    loss_function : "sigmoid",
+    evaluate_metric : ["auc"],
+    just_evaluate : false,
+    regularization : {
+        l1 : [5.28e-9, 5.28e-9],
+        l2 : [5.28e-7, 5.28e-7]
+    }
+},
+
+optimization {
+    optimizer : "line_search",
+
+    line_search {
+
+        mode : "wolfe",
+
+        backtracking : {
+            step_decr : 0.5,
+            step_incr : 2.1,
+            max_iter : 55,
+            min_step : 1e-16,
+            max_step : 1e18,
+            c1 : 1e-4,
+            c2 : 0.9
+        }
+
+        lbfgs {
+            m : 12,
+            convergence : {
+                max_iter : 100,
+                eps : 1e-3
+            }
+        }
+    }
+},
+
+hyper {
+    switch_on : false,
+    restart : true,
+    mode : "hoag",
+
+    hoag {
+        init_step : 1.0,
+        step_decr_factor : 0.7,
+        test_loss_reduce_limit : 1e-5,
+        outer_iter : 10,
+        l1 : [0.0, 0.0],
+        l2 : [5.28e-7, 5.28e-7]
+    },
+
+    grid {
+        l1 : [1e-9, 1e-6, 5, 1e-9, 1e-6, 5],
+        l2 : [1e-8, 1e-5, 5, 1e-8, 1e-5, 5]
+    }
+
+},
+
+random {
+    mode : "normal",
+    seed : 111111,
+    normal {
+        mean : 0.0,
+        std : 0.01
+    },
+
+    uniform {
+        range_start : -0.01,
+        range_end : 0.01
+    },
+},
+
+k : [1,4],
+bias_need_latent_factor : false
+
+

demo/win/ffm/binary_classification/field.dict

@@ -0,0 +1,114 @@
+88
+110
+111
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+90
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+92
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+10
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+99
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+120
+121
+1
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+124
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+125
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+126
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+20
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+100
+101
+102
+105
+106
+107
+80
+108
+81
+109
+82
+83
+84
+85
+86
+87

demo/win/ffm/binary_classification/win_local_optimizer.bat

@@ -0,0 +1,30 @@
+echo on
+@Rem thread number
+set thread_num=6
+
+@Rem use current machine as master
+FOR /F "usebackq" %%i IN (`hostname`) DO SET master_host=%%i
+echo %master_host%
+
+@Rem if you run more than one training tasks on the same host at the same time,
+@Rem different tasks must have different ports!
+set master_port=61235
+
+@Rem model name(linear, fm, ffm, gbdt, gbmlr, gbsdt, gbhmlr, gbhsdt, multiclass_linear)
+set model_name=ffm
+
+@Rem model config
+set properties_path=demo/win/ffm/binary_classification/%model_name%.conf
+
+@Rem train/test line python transform switch & script
+set transform=false
+set transform_script_path=bin/transform.py
+
+cd ../../../../
+@Rem start ytk-mp4j master, default max memory is 512m
+@start /b cmd /c java -Xmx512m -cp lib/* -Dlog4j.configuration=file:config/log4j_master_win.properties com.fenbi.mp4j.comm.CommMaster 1 %master_port%
+
+@Rem start windows train local worker, default max memory is 1000m
+@start /b cmd /c java -Xmx1000m -XX:-OmitStackTraceInFastThrow -cp lib/* -Dlog4j.configuration=file:config/log4j_slave_win.properties com.fenbi.ytklearn.worker.LocalTrainWorker  %model_name% %properties_path% %transform_script_path% %transform% user %master_host% %master_port% %thread_num%
+
+pause