fix: classifier accuracy

[vancauwe]

The classifier currently has issues in its predictions. They do not match the ones stated in its article. Further investigations are needed to understand this accuracy drop.

[rmm-ch]

Test script added, and some outputs from one run (the model predictions aren't deterministic)

terrible performance '(

• note: here the model likes pantropic dolphins and grey whales, though the samples tested are unbalanced
• this used a laptop CPU. See fix: configure model to use GPU #13

Mean load time: 0.035 +- 0.02 s
Mean classify time: 1.079 +- 0.06 s
Accuracy: correct with top prediction: 2 | any of top 3 correct: 5.000 (of total 100)
Which classes are predicted?
pred_0
pantropic_spotted_dolphin    29
gray_whale                   26
white_sided_dolphin          13
beluga                       10
dusky_dolphin                 7
pygmy_killer_whale            6
long_finned_pilot_whale       3
spotted_dolphin               2
common_dolphin                2
false_killer_whale            1
melon_headed_whale            1
Name: count, dtype: int64

# and then check most popular target classes:
print(df_results.target.value_counts().head())

bottlenose_dolphin         18
humpback_whale             18
beluga                     14
blue_whale                 10
melon_headed_whale          7