├── .DS_Store ├── .ipynb_checkpoints ├── cluster_확인v0-checkpoint.ipynb ├── clustering-checkpoint.ipynb ├── corr_v0-checkpoint.ipynb ├── corr_v1_공분산-checkpoint.ipynb ├── corr_v2_시각화-checkpoint.ipynb ├── corr_v3_상자그림-checkpoint.ipynb ├── corr_v4_상관분석 종류-checkpoint.ipynb ├── corr_v5-checkpoint.ipynb ├── corr_v6-checkpoint.ipynb ├── corr_v7_cluster2-checkpoint.ipynb ├── external_result비교-checkpoint.ipynb ├── fa_v0-checkpoint.ipynb ├── fa_v1-checkpoint.ipynb ├── fa_v1.1_knob-checkpoint.ipynb ├── fa_v2_6000_final-checkpoint.ipynb ├── knobs확인v0-checkpoint.ipynb ├── knobs확인v1_normally-checkpoint.ipynb ├── knobs확인v2-checkpoint.ipynb ├── lightgbm-checkpoint.ipynb ├── lightgbm_LGBMClassifier0-checkpoint.ipynb ├── lightgbm_LGBMRegressor0-checkpoint.ipynb ├── lightgbm_lgb0-checkpoint.ipynb ├── model_v0.0-checkpoint.ipynb ├── model_v0.1-checkpoint.ipynb ├── model_v0.2-checkpoint.ipynb ├── model_v0.3_목적함수수정전-checkpoint.ipynb ├── model_v0.3_목적함수수정전2-checkpoint.ipynb ├── model_v0.4-checkpoint.ipynb ├── model_v0.4_4000대-checkpoint.ipynb ├── model_v0.5_6000대_lightgbm-checkpoint.ipynb ├── model_v0.5_6000대_xgb-checkpoint.ipynb ├── model_v0.6_6000대_scaled-checkpoint.ipynb ├── model_v0.71_r10000_rdb_ightgbm-checkpoint.ipynb ├── pca_v0-checkpoint.ipynb ├── randomsample_v0-checkpoint.ipynb ├── test-checkpoint.ipynb └── throughput_비교-checkpoint.ipynb ├── README.md ├── aof_1_1 ├── .DS_Store ├── .ipynb_checkpoints │ ├── corr_v7_cluster2_r10000_aof-checkpoint.ipynb │ ├── fa_v3_r10000_aof-checkpoint.ipynb │ ├── model_v0.71_r10000_aof_lightgbm-checkpoint.ipynb │ ├── model_v0.72_r10000_aof_xgb-checkpoint.ipynb │ ├── model_v0.74_r10000_rdb_decisiontree-checkpoint.ipynb │ ├── model_v0.75_r10000_rdb_gradientboost-checkpoint.ipynb │ ├── model_v0.76_r10000_rdb_randomforest-checkpoint.ipynb │ ├── model_v0.77_r10000_rdb_ridge-checkpoint.ipynb │ ├── model_v0.78_r10000_rdb_lasso-checkpoint.ipynb │ └── model_v0.78_r10000_rdb_linearregression-checkpoint.ipynb ├── README.md ├── corr_v7_cluster2_r10000_aof.ipynb ├── fa_v3_r10000_aof.ipynb ├── model_v0.71_r10000_aof_lightgbm.ipynb ├── model_v0.72_r10000_aof_xgb.ipynb ├── model_v0.74_r10000_rdb_decisiontree.ipynb ├── model_v0.75_r10000_rdb_gradientboost.ipynb ├── model_v0.76_r10000_rdb_randomforest.ipynb ├── model_v0.77_r10000_rdb_ridge.ipynb ├── model_v0.78_r10000_rdb_lasso.ipynb ├── model_v0.78_r10000_rdb_linearregression.ipynb └── test │ ├── .ipynb_checkpoints │ └── Untitled-checkpoint.ipynb │ └── Untitled.ipynb ├── aof_1_2 ├── .DS_Store ├── .ipynb_checkpoints │ ├── corr_v7_cluster2_r10000_aof-checkpoint.ipynb │ ├── fa_v3_r10000_aof-checkpoint.ipynb │ ├── model_v0.71_r10000_aof_lightgbm-checkpoint.ipynb │ ├── model_v0.72_r10000_aof_xgb-checkpoint.ipynb │ ├── model_v0.74_r10000_rdb_decisiontree-checkpoint.ipynb │ ├── model_v0.75_r10000_rdb_gradientboost-checkpoint.ipynb │ ├── model_v0.76_r10000_rdb_randomforest-checkpoint.ipynb │ ├── model_v0.77_r10000_rdb_ridge-checkpoint.ipynb │ ├── model_v0.78_r10000_rdb_lasso-checkpoint.ipynb │ └── model_v0.78_r10000_rdb_linearregression-checkpoint.ipynb ├── README.md ├── corr_v7_cluster2_r10000_aof.ipynb ├── fa_v3_r10000_aof.ipynb ├── model_v0.71_r10000_aof_lightgbm.ipynb ├── model_v0.72_r10000_aof_xgb.ipynb ├── model_v0.74_r10000_rdb_decisiontree.ipynb ├── model_v0.75_r10000_rdb_gradientboost.ipynb ├── model_v0.76_r10000_rdb_randomforest.ipynb ├── model_v0.77_r10000_rdb_ridge.ipynb ├── model_v0.78_r10000_rdb_lasso.ipynb ├── model_v0.78_r10000_rdb_linearregression.ipynb └── test │ ├── .ipynb_checkpoints │ └── Untitled-checkpoint.ipynb │ └── Untitled.ipynb ├── configfile_extract ├── .DS_Store ├── func.py └── knobs.py ├── correlation ├── .DS_Store ├── .ipynb_checkpoints │ ├── corr_v0-checkpoint.ipynb │ ├── corr_v1_공분산-checkpoint.ipynb │ ├── corr_v3_상자그림-checkpoint.ipynb │ ├── corr_v4_상관분석 종류-checkpoint.ipynb │ ├── corr_v5-checkpoint.ipynb │ ├── corr_v6-checkpoint.ipynb │ ├── corr_v7_cluster2-checkpoint.ipynb │ └── corr_v8_cluster2_r10000_rdb-checkpoint.ipynb ├── corr_v0.ipynb ├── corr_v1_공분산.ipynb ├── corr_v2_시각화.ipynb ├── corr_v3_상자그림.ipynb ├── corr_v4_상관분석 종류.ipynb ├── corr_v5.ipynb ├── corr_v6.ipynb ├── corr_v7_cluster2.ipynb └── corr_v8_cluster2_r10000_rdb.ipynb ├── data ├── .DS_Store ├── external_metrics0.csv ├── external_metrics5.csv ├── external_metrics_6000_6.csv ├── external_metrics_r10000_aof.csv ├── external_metrics_r10000_aof1.csv ├── external_metrics_r10000_aof2.csv ├── external_metrics_r10000_rdb.csv ├── external_metrics_r10000_rdb2.csv ├── internal_metrcis0.csv ├── internal_metrcis1.csv ├── internal_metrics4.csv ├── internal_metrics5.csv ├── internal_metrics_6000_6.csv ├── internal_metrics_r10000_aof.csv ├── internal_metrics_r10000_aof1.csv ├── internal_metrics_r10000_aof2.csv ├── internal_metrics_r10000_rdb.csv ├── internal_metrics_r10000_rdb2.csv ├── redis_config_normal4.csv ├── result_config0.csv ├── result_config10001_11000.csv ├── result_config2_normal1.csv ├── result_config3_normal.csv ├── result_config5.csv ├── result_config_6000_6.csv ├── result_config_r10000_aof.csv ├── result_config_r10000_rdb.csv ├── result_rdb_external_4.csv └── result_rdb_internal_4.csv ├── ex1.txt ├── factor_analysis ├── .DS_Store ├── .ipynb_checkpoints │ ├── fa_v0-checkpoint.ipynb │ ├── fa_v1-checkpoint.ipynb │ ├── fa_v2-checkpoint.ipynb │ ├── fa_v3_6000_final-checkpoint.ipynb │ └── fa_v4_r10000_rdb-checkpoint.ipynb ├── fa_v0.ipynb ├── fa_v1.ipynb ├── fa_v2.ipynb ├── fa_v3_6000_final.ipynb └── fa_v4_r10000_rdb.ipynb ├── fig_test12.png ├── knob_check ├── .DS_Store ├── knobs확인v0.ipynb ├── knobs확인v1_normally.ipynb └── knobs확인v2.ipynb ├── model ├── .DS_Store ├── .ipynb_checkpoints │ ├── model_v0.6_6000대_scaled-checkpoint.ipynb │ ├── model_v0.71_r10000_rdb_lightgbm_이상치제거-checkpoint.ipynb │ └── model_v0.72_r10000_rdb_xgb_이상치제거-checkpoint.ipynb ├── lightgbm.ipynb ├── lightgbm_LGBMClassifier0.ipynb ├── lightgbm_LGBMRegressor0.ipynb ├── lightgbm_lgb0.ipynb ├── model_v0.0.ipynb ├── model_v0.1.ipynb ├── model_v0.2.ipynb ├── model_v0.3_목적함수수정전.ipynb ├── model_v0.3_목적함수수정전2.ipynb ├── model_v0.4.ipynb ├── model_v0.4_4000대.ipynb ├── model_v0.5_6000대_lightgbm.ipynb ├── model_v0.5_6000대_xgb.ipynb ├── model_v0.6_6000대_scaled.ipynb ├── model_v0.71_r10000_rdb_lightgbm_이상치제거.ipynb └── model_v0.72_r10000_rdb_xgb_이상치제거.ipynb ├── model_v0.71_r10000_rdb_ightgbm.ipynb ├── rdb_1_1 ├── .DS_Store ├── .ipynb_checkpoints │ ├── corr_v7_cluster2_r10000_rdb-checkpoint.ipynb │ ├── fa_v3_r10000_rdb-checkpoint.ipynb │ ├── model_v0.71_r10000_rdb_lightgbm-checkpoint.ipynb │ ├── model_v0.72_r10000_rdb_xgb-checkpoint.ipynb │ ├── model_v0.74_r10000_rdb_decisiontree-checkpoint.ipynb │ ├── model_v0.75_r10000_rdb_gradientboost-checkpoint.ipynb │ ├── model_v0.76_r10000_rdb_randomforest-checkpoint.ipynb │ ├── model_v0.77_r10000_rdb_ridge-checkpoint.ipynb │ ├── model_v0.78_r10000_rdb_lasso-checkpoint.ipynb │ └── model_v0.78_r10000_rdb_linearregression-checkpoint.ipynb ├── corr_v7_cluster2_r10000_rdb.ipynb ├── fa_v3_r10000_rdb.ipynb ├── model_v0.71_r10000_rdb_lightgbm.ipynb ├── model_v0.72_r10000_rdb_xgb.ipynb ├── model_v0.74_r10000_rdb_decisiontree.ipynb ├── model_v0.75_r10000_rdb_gradientboost.ipynb ├── model_v0.76_r10000_rdb_randomforest.ipynb ├── model_v0.77_r10000_rdb_ridge.ipynb ├── model_v0.78_r10000_rdb_lasso.ipynb └── model_v0.78_r10000_rdb_linearregression.ipynb ├── rdb_1_2 ├── .DS_Store ├── .ipynb_checkpoints │ ├── corr_v7_cluster2_r10000_rdb-checkpoint.ipynb │ ├── fa_v3_r10000_rdb-checkpoint.ipynb │ ├── model_v0.71_r10000_rdb_lightgbm-checkpoint.ipynb │ ├── model_v0.72_r10000_rdb_xgb-checkpoint.ipynb │ ├── model_v0.74_r10000_rdb_decisiontree-checkpoint.ipynb │ ├── model_v0.75_r10000_rdb_gradientboost-checkpoint.ipynb │ ├── model_v0.76_r10000_rdb_randomforest-checkpoint.ipynb │ ├── model_v0.77_r10000_rdb_ridge-checkpoint.ipynb │ ├── model_v0.78_r10000_rdb_lasso-checkpoint.ipynb │ └── model_v0.78_r10000_rdb_linearregression-checkpoint.ipynb ├── corr_v7_cluster2_r10000_rdb.ipynb ├── fa_v3_r10000_rdb.ipynb ├── model_v0.71_r10000_rdb_lightgbm.ipynb ├── model_v0.72_r10000_rdb_xgb.ipynb ├── model_v0.74_r10000_rdb_decisiontree.ipynb ├── model_v0.75_r10000_rdb_gradientboost.ipynb ├── model_v0.76_r10000_rdb_randomforest.ipynb ├── model_v0.77_r10000_rdb_ridge.ipynb ├── model_v0.78_r10000_rdb_lasso.ipynb └── model_v0.78_r10000_rdb_linearregression.ipynb ├── rstudio ├── test.R └── 슬기로운통계생활.R ├── test.ipynb ├── 세미나_발표자료 ├── .DS_Store ├── 20210818_조성운_연구진행사항.pptx ├── 20210823_조성운_연구진행사항.pptx ├── 20210830_조성운_세미나발표자료.pptx ├── 20210906_조성운_세미나발표자료.pptx ├── 20210913_조성운_세미나발표자료.pptx └── 연구주제.pptx └── 연구실 ├── 20210720 ├── .ipynb_checkpoints │ └── pytorch-checkpoint.ipynb ├── 20210727_조성운_세미나발표자료.pptx ├── BO.txt ├── Data Mining Concepts and Techniques 3rd Edition (2012) - Han and Kamber.pdf ├── others.pptx ├── pytorch.ipynb └── ~$20210727_조성운_세미나발표자료.pptx ├── .DS_Store ├── redis-test2 copy 10 ├── .idea │ ├── .gitignore │ ├── inspectionProfiles │ │ └── profiles_settings.xml │ ├── misc.xml │ ├── modules.xml │ └── redis-test2.iml ├── 15.py ├── appendonly.aof ├── config0.conf ├── config1.conf ├── dump.rdb ├── logfile ├── result_config0.txt ├── result_config1.txt └── test.py ├── redis-test2 copy 11 ├── .idea │ ├── .gitignore │ ├── inspectionProfiles │ │ └── profiles_settings.xml │ ├── misc.xml │ ├── modules.xml │ └── redis-test2.iml ├── 15.py ├── appendonly.aof ├── config0.conf ├── config1.conf ├── dump.rdb ├── logfile ├── result_config0.txt ├── result_config1.txt └── test.py ├── redis-test2 copy 9 ├── .idea │ ├── .gitignore │ ├── inspectionProfiles │ │ └── profiles_settings.xml │ ├── misc.xml │ ├── modules.xml │ └── redis-test2.iml ├── 15.py ├── appendonly.aof ├── config0.conf ├── config1.conf ├── dump.rdb ├── logfile ├── result_config0.txt ├── result_config1.txt └── test.py ├── redis-test2 ├── .idea │ ├── .gitignore │ ├── inspectionProfiles │ │ └── profiles_settings.xml │ ├── misc.xml │ ├── modules.xml │ └── redis-test2.iml ├── 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