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This commit is contained in:
FlorianSpeicher
2025-08-15 05:08:06 +02:00
parent ce433bb97f
commit 7421171bb0
41 changed files with 619 additions and 172 deletions
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21
comparisons/AdaBoostClassifier-n50-l0,80.txt
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precision recall f1-score support
0 0.86 0.77 0.82 300
1 0.71 0.52 0.60 216
2 0.50 0.06 0.10 86
3 0.71 0.11 0.19 46
4 0.71 0.24 0.36 83
5 0.00 0.00 0.00 0
6 0.71 0.71 0.71 245
7 0.73 0.19 0.30 42
8 0.83 0.43 0.57 127
9 1.00 0.33 0.50 12
10 0.75 0.52 0.61 127
11 0.38 0.21 0.27 14
12 0.74 0.42 0.54 106
13 0.00 0.00 0.00 0
micro avg 0.76 0.52 0.62 1404
macro avg 0.62 0.32 0.40 1404
weighted avg 0.75 0.52 0.59 1404
samples avg 0.75 0.58 0.61 1404

21
comparisons/AdaBoostClassifier-n50-l1,00.txt
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precision recall f1-score support
0 0.87 0.76 0.81 300
1 0.70 0.59 0.64 216
2 0.58 0.13 0.21 86
3 0.56 0.11 0.18 46
4 0.71 0.30 0.42 83
5 0.00 0.00 0.00 0
6 0.69 0.70 0.69 245
7 0.62 0.31 0.41 42
8 0.76 0.41 0.53 127
9 1.00 0.50 0.67 12
10 0.67 0.50 0.57 127
11 0.40 0.29 0.33 14
12 0.74 0.45 0.56 106
13 0.00 0.00 0.00 0
micro avg 0.74 0.54 0.62 1404
macro avg 0.59 0.36 0.43 1404
weighted avg 0.73 0.54 0.60 1404
samples avg 0.74 0.59 0.61 1404

21
comparisons/AdaBoostClassifier-n50-l2,00.txt
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precision recall f1-score support
0 0.61 0.97 0.75 300
1 0.46 0.93 0.61 216
2 0.23 0.85 0.36 86
3 0.07 0.76 0.14 46
4 0.19 0.94 0.32 83
5 0.00 0.00 0.00 0
6 0.00 0.00 0.00 245
7 0.09 0.69 0.16 42
8 0.26 0.99 0.41 127
9 0.02 0.58 0.05 12
10 0.27 0.80 0.40 127
11 0.03 0.29 0.05 14
12 0.17 0.71 0.27 106
13 0.00 0.00 0.00 0
micro avg 0.24 0.73 0.36 1404
macro avg 0.17 0.61 0.25 1404
weighted avg 0.29 0.73 0.40 1404
samples avg 0.25 0.74 0.35 1404

21
comparisons/BaggingClassifier.txt
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@@ -1,21 +0,0 @@
precision recall f1-score support
0 0.85 0.75 0.80 300
1 0.72 0.52 0.60 216
2 0.70 0.19 0.29 86
3 0.43 0.07 0.11 46
4 0.59 0.16 0.25 83
5 0.00 0.00 0.00 0
6 0.66 0.62 0.64 245
7 0.60 0.29 0.39 42
8 0.73 0.49 0.58 127
9 0.75 0.25 0.38 12
10 0.75 0.49 0.59 127
11 0.67 0.14 0.24 14
12 0.68 0.50 0.58 106
13 0.00 0.00 0.00 0
micro avg 0.73 0.51 0.60 1404
macro avg 0.58 0.32 0.39 1404
weighted avg 0.71 0.51 0.58 1404
samples avg 0.73 0.56 0.59 1404

21
comparisons/ComplementNB-a0,25.txt
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@@ -1,21 +0,0 @@
precision recall f1-score support
0 0.79 0.94 0.86 300
1 0.77 0.60 0.68 216
2 0.55 0.07 0.12 86
3 0.00 0.00 0.00 46
4 0.56 0.06 0.11 83
5 0.00 0.00 0.00 0
6 0.78 0.83 0.80 245
7 0.29 0.05 0.08 42
8 0.90 0.20 0.33 127
9 0.00 0.00 0.00 12
10 0.84 0.29 0.43 127
11 0.25 0.14 0.18 14
12 0.78 0.13 0.23 106
13 0.00 0.00 0.00 0
micro avg 0.76 0.50 0.60 1404
macro avg 0.46 0.24 0.27 1404
weighted avg 0.72 0.50 0.53 1404
samples avg 0.78 0.56 0.61 1404

21
comparisons/ComplementNB-a0,50.txt
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@@ -1,21 +0,0 @@
precision recall f1-score support
0 0.72 0.95 0.82 300
1 0.80 0.47 0.59 216
2 0.75 0.07 0.13 86
3 0.00 0.00 0.00 46
4 0.67 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.78 0.83 0.80 245
7 0.40 0.05 0.09 42
8 0.83 0.04 0.08 127
9 0.00 0.00 0.00 12
10 0.69 0.07 0.13 127
11 0.00 0.00 0.00 14
12 1.00 0.06 0.11 106
13 0.00 0.00 0.00 0
micro avg 0.73 0.44 0.55 1404
macro avg 0.47 0.18 0.20 1404
weighted avg 0.72 0.44 0.45 1404
samples avg 0.75 0.49 0.55 1404

21
comparisons/ComplementNB-a1,00.txt
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precision recall f1-score support
0 0.67 0.98 0.80 300
1 0.81 0.36 0.50 216
2 0.67 0.05 0.09 86
3 0.00 0.00 0.00 46
4 0.80 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.77 0.81 0.79 245
7 0.40 0.05 0.09 42
8 0.83 0.04 0.08 127
9 0.00 0.00 0.00 12
10 0.43 0.02 0.04 127
11 0.00 0.00 0.00 14
12 1.00 0.05 0.09 106
13 0.00 0.00 0.00 0
micro avg 0.70 0.42 0.53 1404
macro avg 0.46 0.17 0.18 1404
weighted avg 0.69 0.42 0.42 1404
samples avg 0.71 0.46 0.52 1404

13
comparisons/MultinomialNB-a0,25.txt
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from sklearn.linear_model import LogisticRegression
from sklearn.naive_bayes import MultinomialNB
from sklearn.multioutput import MultiOutputClassifier
#LogisticRegression(max_iter=1337, random_state=0) -> bad macros
base_clf = MultinomialNB(alpha=0.25)
# n_jobs=1 since there seems to be some multithreading join issue in sklearn (or my pc is to bad)
multi_target_clf = MultiOutputClassifier(base_clf, n_jobs=1)
multi_target_clf.fit(X_train, y_train)
y_pred = multi_target_clf.predict(X_test)

2
comparisons/BernoulliNB-a1,00.txt → games_march2025_cleaned/BernoulliNB.txt
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@@ -19,5 +19,3 @@
macro avg 0.40 0.27 0.30 1404
weighted avg 0.64 0.55 0.56 1404
samples avg 0.73 0.59 0.61 1404
-> this is designed for binary/boolean features, so not for our dataset

21
games_march2025_cleaned/DecisionTreeClassifier.txt Normal file
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precision recall f1-score support
0 0.76 0.73 0.75 300
1 0.56 0.53 0.54 216
2 0.36 0.33 0.34 86
3 0.33 0.26 0.29 46
4 0.40 0.46 0.43 83
5 0.00 0.00 0.00 0
6 0.65 0.61 0.63 245
7 0.39 0.40 0.40 42
8 0.59 0.57 0.58 127
9 0.60 0.25 0.35 12
10 0.56 0.51 0.53 127
11 0.39 0.50 0.44 14
12 0.52 0.49 0.50 106
13 0.00 0.00 0.00 0
micro avg 0.58 0.55 0.57 1404
macro avg 0.44 0.40 0.41 1404
weighted avg 0.58 0.55 0.57 1404
samples avg 0.59 0.59 0.55 1404

0
comparisons/GaussianNB.txt → games_march2025_cleaned/GaussianNB.txt
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21
games_march2025_cleaned/GradientBoostingClassifier.txt Normal file
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precision recall f1-score support
0 0.85 0.80 0.83 300
1 0.77 0.61 0.68 216
2 0.55 0.13 0.21 86
3 0.42 0.11 0.17 46
4 0.68 0.33 0.44 83
5 0.00 0.00 0.00 0
6 0.71 0.76 0.74 245
7 0.61 0.26 0.37 42
8 0.81 0.50 0.61 127
9 0.75 0.25 0.38 12
10 0.81 0.54 0.65 127
11 0.40 0.43 0.41 14
12 0.69 0.42 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.76 0.57 0.65 1404
macro avg 0.57 0.37 0.43 1404
weighted avg 0.74 0.57 0.63 1404
samples avg 0.76 0.63 0.65 1404

21
games_march2025_cleaned/LinearSVC-i5000.txt Normal file
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precision recall f1-score support
0 0.85 0.87 0.86 300
1 0.76 0.66 0.70 216
2 0.77 0.20 0.31 86
3 0.00 0.00 0.00 46
4 0.76 0.27 0.39 83
5 0.00 0.00 0.00 0
6 0.78 0.81 0.79 245
7 0.89 0.19 0.31 42
8 0.77 0.60 0.67 127
9 1.00 0.58 0.74 12
10 0.85 0.54 0.66 127
11 1.00 0.29 0.44 14
12 0.82 0.42 0.56 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.61 0.69 1404
macro avg 0.66 0.39 0.46 1404
weighted avg 0.78 0.61 0.66 1404
samples avg 0.81 0.67 0.69 1404

21
games_march2025_cleaned/LogisticRegression-i1000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned/LogisticRegression-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned/MLPClassifier-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.84 0.85 0.84 300
1 0.73 0.67 0.70 216
2 0.74 0.30 0.43 86
3 0.50 0.02 0.04 46
4 0.69 0.24 0.36 83
5 0.00 0.00 0.00 0
6 0.79 0.79 0.79 245
7 0.86 0.14 0.24 42
8 0.76 0.63 0.69 127
9 1.00 0.33 0.50 12
10 0.81 0.52 0.63 127
11 1.00 0.14 0.25 14
12 0.75 0.41 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.60 0.68 1404
macro avg 0.68 0.36 0.43 1404
weighted avg 0.78 0.60 0.65 1404
samples avg 0.80 0.66 0.68 1404

0
comparisons/MultinomialNB-a1,00.txt → games_march2025_cleaned/MultinomialNB.txt
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21
games_march2025_cleaned/RandomForestClassifier.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.80 0.88 0.84 300
1 0.78 0.55 0.64 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.06 0.11 83
5 0.00 0.00 0.00 0
6 0.74 0.78 0.76 245
7 0.00 0.00 0.00 42
8 0.84 0.24 0.38 127
9 0.00 0.00 0.00 12
10 0.91 0.24 0.38 127
11 1.00 0.14 0.25 14
12 1.00 0.25 0.39 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.48 0.59 1404
macro avg 0.58 0.23 0.27 1404
weighted avg 0.78 0.48 0.52 1404
samples avg 0.77 0.54 0.60 1404

21
games_march2025_cleaned/SVC-RBF-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.81 0.90 0.85 300
1 0.76 0.63 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.77 0.83 0.80 245
7 0.00 0.00 0.00 42
8 0.84 0.40 0.54 127
9 1.00 0.17 0.29 12
10 0.90 0.34 0.49 127
11 1.00 0.14 0.25 14
12 0.92 0.21 0.34 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.53 0.63 1404
macro avg 0.64 0.26 0.32 1404
weighted avg 0.79 0.53 0.56 1404
samples avg 0.79 0.59 0.63 1404

21
games_march2025_cleaned_10k/BernoulliNB.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.75 0.90 0.82 300
1 0.72 0.68 0.70 216
2 0.50 0.08 0.14 86
3 0.27 0.07 0.11 46
4 0.40 0.07 0.12 83
5 0.00 0.00 0.00 0
6 0.77 0.82 0.79 245
7 0.33 0.10 0.15 42
8 0.67 0.40 0.50 127
9 0.00 0.00 0.00 12
10 0.71 0.37 0.49 127
11 0.00 0.00 0.00 14
12 0.49 0.31 0.38 106
13 0.00 0.00 0.00 0
micro avg 0.70 0.55 0.62 1404
macro avg 0.40 0.27 0.30 1404
weighted avg 0.64 0.55 0.56 1404
samples avg 0.73 0.59 0.61 1404

21
games_march2025_cleaned_10k/DecisionTreeClassifier.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.76 0.73 0.75 300
1 0.56 0.53 0.54 216
2 0.36 0.33 0.34 86
3 0.33 0.26 0.29 46
4 0.40 0.46 0.43 83
5 0.00 0.00 0.00 0
6 0.65 0.61 0.63 245
7 0.39 0.40 0.40 42
8 0.59 0.57 0.58 127
9 0.60 0.25 0.35 12
10 0.56 0.51 0.53 127
11 0.39 0.50 0.44 14
12 0.52 0.49 0.50 106
13 0.00 0.00 0.00 0
micro avg 0.58 0.55 0.57 1404
macro avg 0.44 0.40 0.41 1404
weighted avg 0.58 0.55 0.57 1404
samples avg 0.59 0.59 0.55 1404

21
games_march2025_cleaned_10k/GaussianNB.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.76 0.80 0.78 300
1 0.62 0.51 0.56 216
2 0.63 0.14 0.23 86
3 0.17 0.02 0.04 46
4 0.42 0.10 0.16 83
5 0.00 0.00 0.00 0
6 0.68 0.66 0.67 245
7 0.56 0.12 0.20 42
8 0.55 0.33 0.41 127
9 0.67 0.17 0.27 12
10 0.65 0.31 0.42 127
11 1.00 0.14 0.25 14
12 0.53 0.29 0.38 106
13 0.00 0.00 0.00 0
micro avg 0.66 0.47 0.55 1404
macro avg 0.52 0.26 0.31 1404
weighted avg 0.62 0.47 0.51 1404
samples avg 0.67 0.53 0.55 1404

21
games_march2025_cleaned_10k/GradientBoostingClassifier.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.85 0.80 0.83 300
1 0.77 0.61 0.68 216
2 0.55 0.13 0.21 86
3 0.42 0.11 0.17 46
4 0.68 0.33 0.44 83
5 0.00 0.00 0.00 0
6 0.71 0.76 0.74 245
7 0.61 0.26 0.37 42
8 0.81 0.50 0.61 127
9 0.75 0.25 0.38 12
10 0.81 0.54 0.65 127
11 0.40 0.43 0.41 14
12 0.69 0.42 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.76 0.57 0.65 1404
macro avg 0.57 0.37 0.43 1404
weighted avg 0.74 0.57 0.63 1404
samples avg 0.76 0.63 0.65 1404

21
games_march2025_cleaned_10k/LinearSVC-i5000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.85 0.87 0.86 300
1 0.76 0.66 0.70 216
2 0.77 0.20 0.31 86
3 0.00 0.00 0.00 46
4 0.76 0.27 0.39 83
5 0.00 0.00 0.00 0
6 0.78 0.81 0.79 245
7 0.89 0.19 0.31 42
8 0.77 0.60 0.67 127
9 1.00 0.58 0.74 12
10 0.85 0.54 0.66 127
11 1.00 0.29 0.44 14
12 0.82 0.42 0.56 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.61 0.69 1404
macro avg 0.66 0.39 0.46 1404
weighted avg 0.78 0.61 0.66 1404
samples avg 0.81 0.67 0.69 1404

21
games_march2025_cleaned_10k/LogisticRegression-i1000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned_10k/LogisticRegression-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned_10k/MLPClassifier-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.84 0.85 0.84 300
1 0.73 0.67 0.70 216
2 0.74 0.30 0.43 86
3 0.50 0.02 0.04 46
4 0.69 0.24 0.36 83
5 0.00 0.00 0.00 0
6 0.79 0.79 0.79 245
7 0.86 0.14 0.24 42
8 0.76 0.63 0.69 127
9 1.00 0.33 0.50 12
10 0.81 0.52 0.63 127
11 1.00 0.14 0.25 14
12 0.75 0.41 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.60 0.68 1404
macro avg 0.68 0.36 0.43 1404
weighted avg 0.78 0.60 0.65 1404
samples avg 0.80 0.66 0.68 1404

16
comparisons/MultinomialNB-a0,5.txt → games_march2025_cleaned_10k/MultinomialNB.txt
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@@ -1,21 +1,21 @@
precision recall f1-score support
0 0.68 0.97 0.80 300
1 0.82 0.39 0.53 216
0 0.64 0.99 0.78 300
1 0.85 0.24 0.37 216
2 0.60 0.03 0.07 86
3 0.00 0.00 0.00 46
4 0.80 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.78 0.81 0.80 245
6 0.78 0.80 0.79 245
7 0.40 0.05 0.09 42
8 1.00 0.04 0.08 127
9 0.00 0.00 0.00 12
10 0.43 0.02 0.04 127
10 0.20 0.01 0.02 127
11 0.00 0.00 0.00 14
12 1.00 0.05 0.09 106
13 0.00 0.00 0.00 0
micro avg 0.71 0.42 0.53 1404
macro avg 0.47 0.17 0.18 1404
weighted avg 0.71 0.42 0.42 1404
samples avg 0.72 0.47 0.53 1404
micro avg 0.69 0.40 0.51 1404
macro avg 0.45 0.16 0.17 1404
weighted avg 0.68 0.40 0.39 1404
samples avg 0.70 0.44 0.50 1404

21
games_march2025_cleaned_10k/RandomForestClassifier.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.80 0.88 0.84 300
1 0.78 0.55 0.64 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.06 0.11 83
5 0.00 0.00 0.00 0
6 0.74 0.78 0.76 245
7 0.00 0.00 0.00 42
8 0.84 0.24 0.38 127
9 0.00 0.00 0.00 12
10 0.91 0.24 0.38 127
11 1.00 0.14 0.25 14
12 1.00 0.25 0.39 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.48 0.59 1404
macro avg 0.58 0.23 0.27 1404
weighted avg 0.78 0.48 0.52 1404
samples avg 0.77 0.54 0.60 1404

21
games_march2025_cleaned_10k/SVC-RBF-i10000.txt Normal file
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@@ -0,0 +1,21 @@
precision recall f1-score support
0 0.81 0.90 0.85 300
1 0.76 0.63 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.77 0.83 0.80 245
7 0.00 0.00 0.00 42
8 0.84 0.40 0.54 127
9 1.00 0.17 0.29 12
10 0.90 0.34 0.49 127
11 1.00 0.14 0.25 14
12 0.92 0.21 0.34 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.53 0.63 1404
macro avg 0.64 0.26 0.32 1404
weighted avg 0.79 0.53 0.56 1404
samples avg 0.79 0.59 0.63 1404

21
games_march2025_cleaned_2k/BernoulliNB.txt Normal file
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precision recall f1-score support
0 0.75 0.90 0.82 300
1 0.72 0.68 0.70 216
2 0.50 0.08 0.14 86
3 0.27 0.07 0.11 46
4 0.40 0.07 0.12 83
5 0.00 0.00 0.00 0
6 0.77 0.82 0.79 245
7 0.33 0.10 0.15 42
8 0.67 0.40 0.50 127
9 0.00 0.00 0.00 12
10 0.71 0.37 0.49 127
11 0.00 0.00 0.00 14
12 0.49 0.31 0.38 106
13 0.00 0.00 0.00 0
micro avg 0.70 0.55 0.62 1404
macro avg 0.40 0.27 0.30 1404
weighted avg 0.64 0.55 0.56 1404
samples avg 0.73 0.59 0.61 1404

21
games_march2025_cleaned_2k/DecisionTreeClassifier.txt Normal file
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precision recall f1-score support
0 0.76 0.73 0.75 300
1 0.56 0.53 0.54 216
2 0.36 0.33 0.34 86
3 0.33 0.26 0.29 46
4 0.40 0.46 0.43 83
5 0.00 0.00 0.00 0
6 0.65 0.61 0.63 245
7 0.39 0.40 0.40 42
8 0.59 0.57 0.58 127
9 0.60 0.25 0.35 12
10 0.56 0.51 0.53 127
11 0.39 0.50 0.44 14
12 0.52 0.49 0.50 106
13 0.00 0.00 0.00 0
micro avg 0.58 0.55 0.57 1404
macro avg 0.44 0.40 0.41 1404
weighted avg 0.58 0.55 0.57 1404
samples avg 0.59 0.59 0.55 1404

21
games_march2025_cleaned_2k/GaussianNB.txt Normal file
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precision recall f1-score support
0 0.76 0.80 0.78 300
1 0.62 0.51 0.56 216
2 0.63 0.14 0.23 86
3 0.17 0.02 0.04 46
4 0.42 0.10 0.16 83
5 0.00 0.00 0.00 0
6 0.68 0.66 0.67 245
7 0.56 0.12 0.20 42
8 0.55 0.33 0.41 127
9 0.67 0.17 0.27 12
10 0.65 0.31 0.42 127
11 1.00 0.14 0.25 14
12 0.53 0.29 0.38 106
13 0.00 0.00 0.00 0
micro avg 0.66 0.47 0.55 1404
macro avg 0.52 0.26 0.31 1404
weighted avg 0.62 0.47 0.51 1404
samples avg 0.67 0.53 0.55 1404

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games_march2025_cleaned_2k/GradientBoostingClassifier.txt Normal file
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precision recall f1-score support
0 0.85 0.80 0.83 300
1 0.77 0.61 0.68 216
2 0.55 0.13 0.21 86
3 0.42 0.11 0.17 46
4 0.68 0.33 0.44 83
5 0.00 0.00 0.00 0
6 0.71 0.76 0.74 245
7 0.61 0.26 0.37 42
8 0.81 0.50 0.61 127
9 0.75 0.25 0.38 12
10 0.81 0.54 0.65 127
11 0.40 0.43 0.41 14
12 0.69 0.42 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.76 0.57 0.65 1404
macro avg 0.57 0.37 0.43 1404
weighted avg 0.74 0.57 0.63 1404
samples avg 0.76 0.63 0.65 1404

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games_march2025_cleaned_2k/LinearSVC-i5000.txt Normal file
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precision recall f1-score support
0 0.85 0.87 0.86 300
1 0.76 0.66 0.70 216
2 0.77 0.20 0.31 86
3 0.00 0.00 0.00 46
4 0.76 0.27 0.39 83
5 0.00 0.00 0.00 0
6 0.78 0.81 0.79 245
7 0.89 0.19 0.31 42
8 0.77 0.60 0.67 127
9 1.00 0.58 0.74 12
10 0.85 0.54 0.66 127
11 1.00 0.29 0.44 14
12 0.82 0.42 0.56 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.61 0.69 1404
macro avg 0.66 0.39 0.46 1404
weighted avg 0.78 0.61 0.66 1404
samples avg 0.81 0.67 0.69 1404

21
games_march2025_cleaned_2k/LogisticRegression-i1000.txt Normal file
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precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned_2k/LogisticRegression-i10000.txt Normal file
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precision recall f1-score support
0 0.78 0.91 0.84 300
1 0.78 0.62 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.04 0.07 83
5 0.00 0.00 0.00 0
6 0.79 0.81 0.80 245
7 0.00 0.00 0.00 42
8 0.90 0.34 0.49 127
9 0.00 0.00 0.00 12
10 0.89 0.25 0.39 127
11 0.00 0.00 0.00 14
12 0.88 0.14 0.24 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.50 0.61 1404
macro avg 0.50 0.22 0.26 1404
weighted avg 0.77 0.50 0.53 1404
samples avg 0.77 0.56 0.60 1404

21
games_march2025_cleaned_2k/MLPClassifier-i10000.txt Normal file
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precision recall f1-score support
0 0.84 0.85 0.84 300
1 0.73 0.67 0.70 216
2 0.74 0.30 0.43 86
3 0.50 0.02 0.04 46
4 0.69 0.24 0.36 83
5 0.00 0.00 0.00 0
6 0.79 0.79 0.79 245
7 0.86 0.14 0.24 42
8 0.76 0.63 0.69 127
9 1.00 0.33 0.50 12
10 0.81 0.52 0.63 127
11 1.00 0.14 0.25 14
12 0.75 0.41 0.53 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.60 0.68 1404
macro avg 0.68 0.36 0.43 1404
weighted avg 0.78 0.60 0.65 1404
samples avg 0.80 0.66 0.68 1404

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games_march2025_cleaned_2k/MultinomialNB.txt Normal file
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precision recall f1-score support
0 0.64 0.99 0.78 300
1 0.85 0.24 0.37 216
2 0.60 0.03 0.07 86
3 0.00 0.00 0.00 46
4 0.80 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.78 0.80 0.79 245
7 0.40 0.05 0.09 42
8 1.00 0.04 0.08 127
9 0.00 0.00 0.00 12
10 0.20 0.01 0.02 127
11 0.00 0.00 0.00 14
12 1.00 0.05 0.09 106
13 0.00 0.00 0.00 0
micro avg 0.69 0.40 0.51 1404
macro avg 0.45 0.16 0.17 1404
weighted avg 0.68 0.40 0.39 1404
samples avg 0.70 0.44 0.50 1404

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games_march2025_cleaned_2k/RandomForestClassifier.txt Normal file
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precision recall f1-score support
0 0.80 0.88 0.84 300
1 0.78 0.55 0.64 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.06 0.11 83
5 0.00 0.00 0.00 0
6 0.74 0.78 0.76 245
7 0.00 0.00 0.00 42
8 0.84 0.24 0.38 127
9 0.00 0.00 0.00 12
10 0.91 0.24 0.38 127
11 1.00 0.14 0.25 14
12 1.00 0.25 0.39 106
13 0.00 0.00 0.00 0
micro avg 0.79 0.48 0.59 1404
macro avg 0.58 0.23 0.27 1404
weighted avg 0.78 0.48 0.52 1404
samples avg 0.77 0.54 0.60 1404

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games_march2025_cleaned_2k/SVC-RBF-i10000.txt Normal file
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precision recall f1-score support
0 0.81 0.90 0.85 300
1 0.76 0.63 0.69 216
2 1.00 0.03 0.07 86
3 0.00 0.00 0.00 46
4 1.00 0.05 0.09 83
5 0.00 0.00 0.00 0
6 0.77 0.83 0.80 245
7 0.00 0.00 0.00 42
8 0.84 0.40 0.54 127
9 1.00 0.17 0.29 12
10 0.90 0.34 0.49 127
11 1.00 0.14 0.25 14
12 0.92 0.21 0.34 106
13 0.00 0.00 0.00 0
micro avg 0.80 0.53 0.63 1404
macro avg 0.64 0.26 0.32 1404
weighted avg 0.79 0.53 0.56 1404
samples avg 0.79 0.59 0.63 1404