Only one submission per participant and day is shown. If several submissions are submitted from the same participant in the same day, only the latest one is shown. Submissions made today will be shown from tomorrow.
| Position | Group | Performance | Comment (by the group) | Date |
|---|---|---|---|---|
| 1 | 107 | 0.825 | 9 feature kNN | 2026-09-28 |
| 2 | 25 | 0.82 | RF all features | 2026-10-01 |
| 2 | 106 | 0.82 | Random forest 6 f | 2026-10-02 |
| 2 | 73 | 0.82 | SVM1 | 2026-10-02 |
| 2 | 56 | 0.82 | RFv | 2026-10-02 |
| 2 | 68 | 0.82 | rf all features TN | 2026-10-04 |
| 3 | 5 | 0.815 | knn7n5k | 2026-09-29 |
| 3 | 108 | 0.815 | MO RF3, 13 | 2026-10-04 |
| 3 | 31 | 0.815 | SVM (RBF) | 2026-10-05 |
| 3 | 108 | 0.815 | RF MO 3, 1/5 | 2026-10-05 |
| 4 | 9 | 0.81 | KNN | 2026-09-21 |
| 4 | 10 | 0.81 | Random Forest | 2026-09-21 |
| 4 | 107 | 0.81 | 5 feature RF | 2026-09-24 |
| 4 | 12 | 0.81 | RF | 2026-09-26 |
| 4 | 57 | 0.81 | RF | 2026-09-28 |
| 4 | 12 | 0.81 | Random Forest | 2026-09-29 |
| 4 | 106 | 0.81 | Random forest 7 f | 2026-09-30 |
| 4 | 74 | 0.81 | Bagging | 2026-10-01 |
| 4 | 19 | 0.81 | Random forest - "key" OneHotEncoded | 2026-10-01 |
| 4 | 27 | 0.81 | RandomForest-CV13_AE | 2026-10-02 |
| 4 | 69 | 0.81 | RF with numeric features only (permutation imporances said they did not matter) | 2026-10-04 |
| 4 | 16 | 0.81 | RF ov | 2026-10-04 |
| 4 | 30 | 0.81 | 5F KNN | 2026-10-04 |
| 4 | 105 | 0.81 | 2026-10-04 | |
| 4 | 24 | 0.81 | RandomForest_Final | 2026-10-04 |
| 4 | 78 | 0.81 | SVM 7 features | 2026-10-04 |
| 5 | 99 | 0.805 | rand_forest_100 | 2026-09-15 |
| 5 | 83 | 0.805 | Skog2 | 2026-09-17 |
| 5 | 21 | 0.805 | randomforest CA | 2026-09-21 |
| 5 | 23 | 0.805 | RF 1 | 2026-09-24 |
| 5 | 106 | 0.805 | Random forest 10 f | 2026-09-24 |
| 5 | 106 | 0.805 | Random forest 11 f | 2026-09-25 |
| 5 | 95 | 0.805 | RF_M | 2026-09-26 |
| 5 | 95 | 0.805 | RF_M2 | 2026-09-29 |
| 5 | 24 | 0.805 | 2026-09-30 | |
| 5 | 22 | 0.805 | 2026-10-01 | |
| 5 | 85 | 0.805 | RF all features | 2026-10-02 |
| 5 | 99 | 0.805 | 7nn5feet | 2026-10-02 |
| 5 | 41 | 0.805 | rf123 | 2026-10-04 |
| 5 | 64 | 0.805 | other seed | 2026-10-04 |
| 5 | 63 | 0.805 | Tuned RF (late submish) | 2026-10-05 |
| 5 | 105 | 0.805 | RaNdOm FoReSt | 2026-10-06 |
| 6 | 5 | 0.8 | 2026-09-15 | |
| 6 | 46 | 0.8 | Gradient boosting | 2026-09-22 |
| 6 | 40 | 0.8 | KNN, XGB, and SVM ensemble vote | 2026-09-22 |
| 6 | 40 | 0.8 | KNN, XGB, and SVM ensemble vote | 2026-09-23 |
| 6 | 106 | 0.8 | Random forest 10 f WE | 2026-09-27 |
| 6 | 57 | 0.8 | SVM + Extra Trees | 2026-09-29 |
| 6 | 106 | 0.8 | Random forest 8 f | 2026-09-29 |
| 6 | 86 | 0.8 | 6-feature 5-NN | 2026-09-29 |
| 6 | 61 | 0.8 | RF | 2026-09-30 |
| 6 | 21 | 0.8 | Knn7n5fCA | 2026-09-30 |
| 6 | 101 | 0.8 | rf_ft | 2026-09-30 |
| 6 | 101 | 0.8 | rf_ft | 2026-10-01 |
| 6 | 60 | 0.8 | randomforest | 2026-10-01 |
| 6 | 68 | 0.8 | 2026-10-01 | |
| 6 | 89 | 0.8 | 10 feature 5NN | 2026-10-02 |
| 6 | 58 | 0.8 | 16-NN 5 features | 2026-10-02 |
| 6 | 91 | 0.8 | bg_dct_sne_3 | 2026-10-02 |
| 6 | 54 | 0.8 | RandomForestSecond | 2026-10-02 |
| 6 | 60 | 0.8 | randomforest | 2026-10-02 |
| 6 | 99 | 0.8 | 17nn5feet | 2026-10-03 |
| 6 | 100 | 0.8 | RF-n300md8 | 2026-10-03 |
| 6 | 80 | 0.8 | knn-minus-2 | 2026-10-03 |
| 6 | 66 | 0.8 | RandomSkog | 2026-10-03 |
| 6 | 74 | 0.8 | KNN_2.0 | 2026-10-03 |
| 6 | 60 | 0.8 | randomforest | 2026-10-03 |
| 6 | 31 | 0.8 | Chosen Random forest. | 2026-10-04 |
| 6 | 94 | 0.8 | 7fea forest | 2026-10-04 |
| 6 | 34 | 0.8 | Xgboosts w/ feat engineering | 2026-10-04 |
| 6 | 13 | 0.8 | G3RC | 2026-10-04 |
| 6 | 29 | 0.8 | RF with 150 trees and numerical features | 2026-10-04 |
| 6 | 84 | 0.8 | Random Forest 40% | 2026-10-04 |
| 7 | 99 | 0.795 | rand_forest_80 | 2026-09-16 |
| 7 | 9 | 0.795 | RandomForestClassifier 100 | 2026-09-18 |
| 7 | 40 | 0.795 | KNN, XGB, and LogReg ensemble vote | 2026-09-21 |
| 7 | 21 | 0.795 | KNNCA | 2026-09-22 |
| 7 | 106 | 0.795 | Random forest 10 f Tuned | 2026-09-26 |
| 7 | 5 | 0.795 | rf | 2026-09-28 |
| 7 | 76 | 0.795 | RF_mc | 2026-09-29 |
| 7 | 99 | 0.795 | knn2520 | 2026-09-30 |
| 7 | 45 | 0.795 | SVC - 5 features | 2026-09-30 |
| 7 | 12 | 0.795 | KNN-7 features | 2026-09-30 |
| 7 | 103 | 0.795 | RF | 2026-09-30 |
| 7 | 74 | 0.795 | random forest | 2026-09-30 |
| 7 | 40 | 0.795 | 2026-10-01 | |
| 7 | 66 | 0.795 | KNN14M | 2026-10-01 |
| 7 | 54 | 0.795 | RandomForest | 2026-10-01 |
| 7 | 68 | 0.795 | random forest all features | 2026-10-02 |
| 7 | 74 | 0.795 | Random Forest_2.0 | 2026-10-02 |
| 7 | 13 | 0.795 | G3FCRC | 2026-10-02 |
| 7 | 57 | 0.795 | RF + RBF SVM | 2026-10-02 |
| 7 | 64 | 0.795 | Ensemble KNN + GradientBoosting + RF | 2026-10-03 |
| 7 | 54 | 0.795 | KNNThid | 2026-10-03 |
| 7 | 71 | 0.795 | Randomforest | 2026-10-03 |
| 7 | 30 | 0.795 | 5F KNN | 2026-10-03 |
| 7 | 43 | 0.795 | Neural net | 2026-10-04 |
| 7 | 91 | 0.795 | bg_dct_sne_4 | 2026-10-04 |
| 8 | 98 | 0.79 | funlab3 | 2026-09-21 |
| 8 | 98 | 0.79 | funlab4 | 2026-09-22 |
| 8 | 17 | 0.79 | KNN22 | 2026-09-24 |
| 8 | 107 | 0.79 | 10 feature RF | 2026-09-25 |
| 8 | 91 | 0.79 | Bg_knn_sne | 2026-09-25 |
| 8 | 106 | 0.79 | Random forest 10 f MF=2 | 2026-09-28 |
| 8 | 49 | 0.79 | Ensemble of Random Forest and SVC, 11 features | 2026-09-29 |
| 8 | 102 | 0.79 | SVM C=200 | 2026-09-29 |
| 8 | 10 | 0.79 | knn | 2026-09-29 |
| 8 | 58 | 0.79 | Random forest - 10 features | 2026-09-30 |
| 8 | 49 | 0.79 | Random forest with n=80, 9 features | 2026-09-30 |
| 8 | 91 | 0.79 | bg_knn_sne_2 | 2026-09-30 |
| 8 | 95 | 0.79 | KNN 7_PCA | 2026-10-01 |
| 8 | 99 | 0.79 | nn15-6feet | 2026-10-01 |
| 8 | 10 | 0.79 | lr | 2026-10-01 |
| 8 | 51 | 0.79 | SVM all features, RBF, C=1, gamma=0.01 | 2026-10-02 |
| 8 | 16 | 0.79 | 9nn 5 features ov | 2026-10-03 |
| 8 | 47 | 0.79 | Random Forest MD11 | 2026-10-03 |
| 8 | 43 | 0.79 | XGB | 2026-10-03 |
| 8 | 10 | 0.79 | rf all | 2026-10-03 |
| 8 | 67 | 0.79 | Voting - cn | 2026-10-04 |
| 8 | 97 | 0.79 | Random Forest | 2026-10-04 |
| 8 | 28 | 0.79 | random forest, all features except for key | 2026-10-04 |
| 8 | 89 | 0.79 | 5NN 10 features | 2026-10-04 |
| 8 | 80 | 0.79 | RF ööö | 2026-10-04 |
| 8 | 10 | 0.79 | rf300 | 2026-10-04 |
| 9 | 21 | 0.785 | KNN23 meow ^_^ | 2026-09-29 |
| 9 | 35 | 0.785 | GBv2 | 2026-09-30 |
| 9 | 94 | 0.785 | RandomForest | 2026-10-01 |
| 9 | 5 | 0.785 | knn9 | 2026-10-01 |
| 9 | 100 | 0.785 | 5feat 15-nn | 2026-10-02 |
| 9 | 49 | 0.785 | Random forest n=56, 8 features | 2026-10-02 |
| 9 | 27 | 0.785 | RandomForest-11F_AE | 2026-10-03 |
| 9 | 89 | 0.785 | 10 feature forest | 2026-10-03 |
| 9 | 104 | 0.785 | random forest | 2026-10-03 |
| 9 | 94 | 0.785 | Random forest (0.5,4) | 2026-10-03 |
| 9 | 22 | 0.785 | random Forest | 2026-10-03 |
| 9 | 18 | 0.785 | ov | 2026-10-04 |
| 9 | 59 | 0.785 | RandomForest | 2026-10-04 |
| 9 | 87 | 0.785 | RandomForest | 2026-10-04 |
| 9 | 74 | 0.785 | SVM_2.0 | 2026-10-04 |
| 9 | 31 | 0.785 | KNN | 2026-10-06 |
| 9 | 91 | 0.785 | RF_5feat_sne | 2026-10-10 |
| 10 | 91 | 0.78 | Rand_Forest_sne | 2026-09-14 |
| 10 | 91 | 0.78 | bg_dct_sne_2 | 2026-09-20 |
| 10 | 35 | 0.78 | GradientBoosting | 2026-09-21 |
| 10 | 42 | 0.78 | Random forest 500 | 2026-09-21 |
| 10 | 81 | 0.78 | SVM_top7feat_minustempo | 2026-09-22 |
| 10 | 17 | 0.78 | RF5n600 | 2026-09-28 |
| 10 | 43 | 0.78 | 2026-09-29 | |
| 10 | 47 | 0.78 | randomForest40 | 2026-09-29 |
| 10 | 73 | 0.78 | RandomForest3 | 2026-09-30 |
| 10 | 67 | 0.78 | svm cn | 2026-10-01 |
| 10 | 20 | 0.78 | 3 diverse models | 2026-10-01 |
| 10 | 26 | 0.78 | RF_*feature_200tree | 2026-10-02 |
| 10 | 33 | 0.78 | KNN all featrures- k = 18 | 2026-10-03 |
| 10 | 25 | 0.78 | tuned RF | 2026-10-03 |
| 10 | 44 | 0.78 | random forest | 2026-10-04 |
| 10 | 71 | 0.78 | Random Forest (scoring accuracy) | features = ['loudness', 'acousticness', 'speechiness', 'energy', 'danceability'] | 2026-10-04 |
| 10 | 33 | 0.78 | logreg | 2026-10-04 |
| 11 | 99 | 0.775 | rand_forest_80_rfe6 | 2026-09-17 |
| 11 | 9 | 0.775 | RandomForestClassifier 100 JUA | 2026-09-19 |
| 11 | 91 | 0.775 | bg_dct_sne | 2026-09-19 |
| 11 | 73 | 0.775 | RandomForest1 | 2026-09-23 |
| 11 | 9 | 0.775 | 2026-09-30 | |
| 11 | 58 | 0.775 | SVM - 7 features, C =3 | 2026-10-01 |
| 11 | 43 | 0.775 | knn with 06 | 2026-10-01 |
| 11 | 34 | 0.775 | XGBoosts | 2026-10-02 |
| 11 | 79 | 0.775 | Random Forest A: five numerical features | 2026-10-04 |
| 11 | 9 | 0.775 | 6F-RF | 2026-10-04 |
| 12 | 99 | 0.77 | randfor2 | 2026-09-25 |
| 12 | 99 | 0.77 | adaboo | 2026-09-29 |
| 12 | 43 | 0.77 | 13fKNN | 2026-09-30 |
| 12 | 98 | 0.77 | funlab5 | 2026-10-04 |
| 13 | 99 | 0.765 | sfs_for_md8 | 2026-09-21 |
| 13 | 99 | 0.765 | randfor1 | 2026-09-24 |
| 13 | 99 | 0.765 | RF md8 mf0.5 | 2026-09-28 |
| 13 | 49 | 0.765 | Random forest 30 | 2026-09-28 |
| 13 | 95 | 0.765 | KNN 5ft | 2026-09-30 |
| 13 | 16 | 0.765 | kNN 7 features | 2026-10-01 |
| 13 | 106 | 0.765 | Log reg UE | 2026-10-03 |
| 13 | 86 | 0.765 | 5-feature LogReg with scaling. Please work | 2026-10-03 |
| 13 | 36 | 0.765 | Random forest | 2026-10-04 |
| 13 | 63 | 0.765 | Random forest all feat | 2026-10-04 |
| 14 | 106 | 0.76 | Log reg ME | 2026-10-01 |
| 15 | 10 | 0.755 | RF200/PF | 2026-09-28 |
| 16 | 17 | 0.75 | KNN | 2026-09-17 |
| 16 | 13 | 0.75 | G3KNNMM | 2026-09-30 |
| 16 | 9 | 0.75 | 13NN,3Featurres | 2026-10-03 |
| 17 | 47 | 0.745 | 2026-09-19 | |
| 17 | 67 | 0.745 | knn=9 | 2026-09-29 |
| 17 | 86 | 0.745 | 5-feature 7-NN with scaling | 2026-09-30 |
| 17 | 86 | 0.745 | 5-feature 7-NN with scaling, but pasted correctly | 2026-10-01 |
| 17 | 13 | 0.745 | G3KNNRB | 2026-10-01 |
| 17 | 38 | 0.745 | 2026-10-04 | |
| 18 | 45 | 0.74 | kNN - 6 features | 2026-09-29 |
| 18 | 18 | 0.74 | logreg ov | 2026-10-01 |
| 19 | 73 | 0.735 | RandomForest2 | 2026-09-29 |
| 19 | 45 | 0.735 | kNN - 5 features | 2026-10-01 |
| 20 | 101 | 0.73 | random forest | 2026-09-25 |
| 21 | 83 | 0.68 | 2026-09-14 | |
| 22 | 102 | 0.58 | 2026-09-28 |
You should carefully use the training data to select ONE (1) method (out of 5 or so) which you want to test 'in production' by submitting its predictions to this page. In order to complete the competition, it is thus necessary to submit only ONE (1) contribution during the entire competition!
If you want to improve your solution and compete with the other participants, you are, however, allowed to submit up to one new solution per day. The competition is just for fun, your score on the leader board will not be used in any way to determine your grade on the competition. The grading is based solely on your implementation, conveyed understanding, and the quality of the written report.