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Confusion matrix #78

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f7a8346
added confusion matrix to the output
Apr 18, 2024
3d1ef1e
added labels to the output for the confusion matrix
Apr 19, 2024
f0f6214
changed labels to lower case
Apr 29, 2024
f749e25
Merge branch 'main' into confusion_matrix
Codyk12 May 1, 2024
c7d198b
sorted labels
May 2, 2024
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2 changes: 2 additions & 0 deletions superpipe/grid_search.py
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Original file line number Diff line number Diff line change
Expand Up @@ -115,6 +115,8 @@ def run(self, df: pd.DataFrame, output_dir=None, verbose=False, styled=True):
result = {
**GridSearch._flatten_params_dict(params),
'score': self.pipeline.score,
'lables': self.pipeline.labels,
'Confusion_matrix': self.pipeline.cm,
'input_cost': self.pipeline.statistics.input_cost,
'output_cost': self.pipeline.statistics.output_cost,
'total_latency': self.pipeline.statistics.total_latency,
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8 changes: 8 additions & 0 deletions superpipe/pipeline.py
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Expand Up @@ -7,11 +7,13 @@
from prettytable import PrettyTable
from superpipe.steps import Step, LLMStep, LLMStructuredStep, LLMStructuredCompositeStep
from superpipe.config import is_dev, studio_enabled
from sklearn.metrics import confusion_matrix


@dataclass
class PipelineStatistics:
score: Optional[float] = None
cm = None
input_tokens: dict = field(default_factory=lambda: defaultdict(int))
output_tokens: dict = field(default_factory=lambda: defaultdict(int))
input_cost: float = 0.0
Expand Down Expand Up @@ -68,6 +70,8 @@ def __init__(self,
self.output_fields = output_fields or steps[-1].output_fields()
self.data = None
self.score = None
self.labels = None
self.cm = None
self.name = name or self.__class__.__name__
self.statistics = PipelineStatistics()

Expand Down Expand Up @@ -138,6 +142,10 @@ def evaluate(self, evaluation_fn=None):
results = self.data.apply(lambda row: evaluation_fn(row), axis=1)
self.data[f"__{evaluation_fn.__name__}__"] = results
self.score = results.sum() / len(results)
labels = self.data.label.str.lower()
predicts = self.data.predict.str.lower()
self.labels = sorted(list(set(labels).union(predicts)))
self.cm = confusion_matrix(labels, predicts)
return self.score

def _aggregate_statistics(self, data: Union[pd.DataFrame, Dict]):
Expand Down