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Makefile.gbm_bagging_40_7_0.1_feature10
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include Makefile.feature.feature10
N = 40
DEPTH = 7
LRATE = 0.1
ALGO_NAME := gbm_bagging_$(N)_$(DEPTH)_$(LRATE)
MODEL_NAME := $(ALGO_NAME)_$(FEATURE_NAME)
METRIC_VAL := $(DIR_METRIC)/$(MODEL_NAME).val.txt
PREDICT_VAL := $(DIR_VAL)/$(MODEL_NAME).val.csv
PREDICT_TST := $(DIR_TST)/$(MODEL_NAME).tst.csv
PREDICT_VAL00 := $(DIR_VAL)/$(MODEL_NAME).val00.csv
PREDICT_TST00 := $(DIR_TST)/$(MODEL_NAME).tst00.csv
PREDICT_VAL01 := $(DIR_VAL)/$(MODEL_NAME).val01.csv
PREDICT_TST01 := $(DIR_TST)/$(MODEL_NAME).tst01.csv
PREDICT_VAL02 := $(DIR_VAL)/$(MODEL_NAME).val02.csv
PREDICT_TST02 := $(DIR_TST)/$(MODEL_NAME).tst02.csv
PREDICT_VAL03 := $(DIR_VAL)/$(MODEL_NAME).val03.csv
PREDICT_TST03 := $(DIR_TST)/$(MODEL_NAME).tst03.csv
PREDICT_VAL04 := $(DIR_VAL)/$(MODEL_NAME).val04.csv
PREDICT_TST04 := $(DIR_TST)/$(MODEL_NAME).tst04.csv
PREDICT_VAL05 := $(DIR_VAL)/$(MODEL_NAME).val05.csv
PREDICT_TST05 := $(DIR_TST)/$(MODEL_NAME).tst05.csv
PREDICT_VAL06 := $(DIR_VAL)/$(MODEL_NAME).val06.csv
PREDICT_TST06 := $(DIR_TST)/$(MODEL_NAME).tst06.csv
PREDICT_VAL07 := $(DIR_VAL)/$(MODEL_NAME).val07.csv
PREDICT_TST07 := $(DIR_TST)/$(MODEL_NAME).tst07.csv
PREDICT_VAL08 := $(DIR_VAL)/$(MODEL_NAME).val08.csv
PREDICT_TST08 := $(DIR_TST)/$(MODEL_NAME).tst08.csv
PREDICT_VAL09 := $(DIR_VAL)/$(MODEL_NAME).val09.csv
PREDICT_TST09 := $(DIR_TST)/$(MODEL_NAME).tst09.csv
PREDICT_VAL10 := $(DIR_VAL)/$(MODEL_NAME).val10.csv
PREDICT_TST10 := $(DIR_TST)/$(MODEL_NAME).tst10.csv
PREDICT_VAL11 := $(DIR_VAL)/$(MODEL_NAME).val11.csv
PREDICT_TST11 := $(DIR_TST)/$(MODEL_NAME).tst11.csv
PREDICT_VAL12 := $(DIR_VAL)/$(MODEL_NAME).val12.csv
PREDICT_TST12 := $(DIR_TST)/$(MODEL_NAME).tst12.csv
PREDICT_VAL13 := $(DIR_VAL)/$(MODEL_NAME).val13.csv
PREDICT_TST13 := $(DIR_TST)/$(MODEL_NAME).tst13.csv
SUBMISSION_TST := $(DIR_TST)/$(MODEL_NAME).sub.csv
all: validation submission
validation: $(METRIC_VAL)
submission: $(SUBMISSION_TST)
retrain: clean_$(ALGO_NAME) submission
$(PREDICT_TST00) $(PREDICT_VAL00): $(FEATURE_TRN00) $(FEATURE_TST00) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL00) \
--predict-test-file $(PREDICT_TST00) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST01) $(PREDICT_VAL01): $(FEATURE_TRN01) $(FEATURE_TST01) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL01) \
--predict-test-file $(PREDICT_TST01) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST02) $(PREDICT_VAL02): $(FEATURE_TRN02) $(FEATURE_TST02) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL02) \
--predict-test-file $(PREDICT_TST02) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST03) $(PREDICT_VAL03): $(FEATURE_TRN03) $(FEATURE_TST03) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL03) \
--predict-test-file $(PREDICT_TST03) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST04) $(PREDICT_VAL04): $(FEATURE_TRN04) $(FEATURE_TST04) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL04) \
--predict-test-file $(PREDICT_TST04) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST05) $(PREDICT_VAL05): $(FEATURE_TRN05) $(FEATURE_TST05) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL05) \
--predict-test-file $(PREDICT_TST05) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST06) $(PREDICT_VAL06): $(FEATURE_TRN06) $(FEATURE_TST06) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL06) \
--predict-test-file $(PREDICT_TST06) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST07) $(PREDICT_VAL07): $(FEATURE_TRN07) $(FEATURE_TST07) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL07) \
--predict-test-file $(PREDICT_TST07) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST08) $(PREDICT_VAL08): $(FEATURE_TRN08) $(FEATURE_TST08) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL08) \
--predict-test-file $(PREDICT_TST08) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST09) $(PREDICT_VAL09): $(FEATURE_TRN09) $(FEATURE_TST09) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL09) \
--predict-test-file $(PREDICT_TST09) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST10) $(PREDICT_VAL10): $(FEATURE_TRN10) $(FEATURE_TST10) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL10) \
--predict-test-file $(PREDICT_TST10) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST11) $(PREDICT_VAL11): $(FEATURE_TRN11) $(FEATURE_TST11) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL11) \
--predict-test-file $(PREDICT_TST11) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST12) $(PREDICT_VAL12): $(FEATURE_TRN12) $(FEATURE_TST12) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL12) \
--predict-test-file $(PREDICT_TST12) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(PREDICT_TST13) $(PREDICT_VAL13): $(FEATURE_TRN13) $(FEATURE_TST13) \
| $(DIR_VAL) $(DIR_TST)
./src/train_predict_gbm_bagging.py --train-file $< \
--test-file $(word 2, $^) \
--predict-valid-file $(PREDICT_VAL13) \
--predict-test-file $(PREDICT_TST13) \
--depth $(DEPTH) \
--lrate $(LRATE) \
--n-est $(N)
$(SUBMISSION_TST): $(PREDICT_TST) $(HEADER) $(ID_TST) | $(DIR_TST)
paste -d, $(lastword $^) $< > [email protected]
cat $(word 2, $^) [email protected] > $@
$(PREDICT_VAL): $(PREDICT_VAL00) $(PREDICT_VAL01) $(PREDICT_VAL02) \
$(PREDICT_VAL03) $(PREDICT_VAL04) $(PREDICT_VAL05) \
$(PREDICT_VAL06) $(PREDICT_VAL07) $(PREDICT_VAL08) \
$(PREDICT_VAL09) $(PREDICT_VAL10) $(PREDICT_VAL11) \
$(PREDICT_VAL12) $(PREDICT_VAL13)
paste -d, $^ > $@
$(PREDICT_TST): $(PREDICT_TST00) $(PREDICT_TST01) $(PREDICT_TST02) \
$(PREDICT_TST03) $(PREDICT_TST04) $(PREDICT_TST05) \
$(PREDICT_TST06) $(PREDICT_TST07) $(PREDICT_TST08) \
$(PREDICT_TST09) $(PREDICT_TST10) $(PREDICT_TST11) \
$(PREDICT_TST12) $(PREDICT_TST13)
paste -d, $^ > $@
$(METRIC_VAL): $(PREDICT_VAL) $(YS_TRN) | $(DIR_METRIC)
./src/evaluate.py -t $(lastword $^) -p $< > $@
cat $@
clean:: clean_$(ALGO_NAME)
clean_$(ALGO_NAME):
-rm $(METRIC_VAL) $(PREDICT_VAL) $(PREDICT_TST) $(SUBMISSION_TST)
find . -name '*.pyc' -delete
.DEFAULT_GOAL := all