Here is the current output of python plot_graphs.py
Found new best metric with :{'gamma': 0.01, 'C': 0.1}
New best val metric:0.08839779005524862
Found new best metric with :{'gamma': 0.01, 'C': 0.5}
New best val metric:0.23756906077348067
Found new best metric with :{'gamma': 0.01, 'C': 0.7}
New best val metric:0.4696132596685083
Found new best metric with :{'gamma': 0.01, 'C': 1}
New best val metric:0.8397790055248618
Found new best metric with :{'gamma': 0.01, 'C': 2}
New best val metric:0.856353591160221
Found new best metric with :{'gamma': 0.005, 'C': 0.5}
New best val metric:0.9613259668508287
Found new best metric with :{'gamma': 0.005, 'C': 0.7}
New best val metric:0.9834254143646409
Found new best metric with :{'gamma': 0.001, 'C': 0.7}
New best val metric:0.988950276243094
Found new best metric with :{'gamma': 0.0001, 'C': 5}
New best val metric:0.994475138121547
Classification report for classifier SVC(C=10, gamma=0.0001):
precision recall f1-score support
0 1.00 1.00 1.00 15
1 0.96 1.00 0.98 22
2 1.00 1.00 1.00 13
3 1.00 0.93 0.96 14
4 1.00 0.89 0.94 18
5 1.00 0.94 0.97 18
6 1.00 1.00 1.00 16
7 1.00 1.00 1.00 15
8 0.96 0.96 0.96 26
9 0.88 1.00 0.94 22
accuracy 0.97 179
macro avg 0.98 0.97 0.98 179
weighted avg 0.97 0.97 0.97 179
Best hyperparameters were:
{'gamma': 0.0001, 'C': 5}
docker build -t exp:v1 -f docker/Dockerfile .
docker run -it exp:v1
export FLASK_APP=api/app.py ; flask run