mirror of
https://github.com/Doctorado-ML/Stree_datasets.git
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117 lines
3.4 KiB
Python
117 lines
3.4 KiB
Python
from experimentation.Sets import Datasets
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from experimentation.Utils import TextColor
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from experimentation.Database import MySQL
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models = ["stree", "odte", "adaBoost", "bagging"]
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title = "Best model results"
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lengths = (30, 9, 11, 11, 11, 11)
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def report_header_content(title):
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length = sum(lengths) + len(lengths) - 1
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output = "\n" + "*" * length + "\n"
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num = (length - len(title) - 2) // 2
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num2 = length - len(title) - 2 - 2 * num
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output += "*" + " " * num + title + " " * (num + num2) + "*\n"
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output += "*" * length + "\n\n"
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lines = ""
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for item, data in enumerate(fields):
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output += f"{fields[item]:{lengths[item]}} "
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lines += "=" * lengths[item] + " "
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output += f"\n{lines}"
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return output
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def report_header(exclude_params):
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print(TextColor.HEADER + report_header_content(title) + TextColor.ENDC)
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def report_line(line):
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output = f"{line['dataset']:{lengths[0] + 5}s} "
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data = models.copy()
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data.insert(0, "reference")
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for key, model in enumerate(data):
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output += f"{line[model]:{lengths[key + 1]}s} "
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return output
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def report_footer(agg):
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print(
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TextColor.GREEN
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+ f"we have better results {agg['better']['items']:2d} times"
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)
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print(
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TextColor.RED
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+ f"we have worse results {agg['worse']['items']:2d} times"
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)
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color = TextColor.LINE1
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for item in models:
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print(
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color + f"{item:10s} used {agg[item]['items']:2d} times ", end=""
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)
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print(
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color + f"better {agg[item]['better']:2d} times ",
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end="",
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)
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print(color + f"worse {agg[item]['worse']:2d} times ")
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color = (
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TextColor.LINE2 if color == TextColor.LINE1 else TextColor.LINE1
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)
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dbh = MySQL()
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database = dbh.get_connection()
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dt = Datasets(False, False, "tanveer")
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fields = ("Dataset", "Reference")
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for model in models:
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fields += (f"{model}",)
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report_header(title)
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color = TextColor.LINE1
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agg = {}
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for item in [
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"better",
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"worse",
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] + models:
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agg[item] = {}
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agg[item]["items"] = 0
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agg[item]["better"] = 0
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agg[item]["worse"] = 0
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for dataset in dt:
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find_one = False
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line = {"dataset": color + dataset[0]}
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record = dbh.find_best(dataset[0], "any")
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max_accuracy = 0.0 if record is None else record[5]
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for model in models:
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record = dbh.find_best(dataset[0], model)
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if record is None:
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line[model] = color + "-" * 9 + " "
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else:
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reference = record[10]
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accuracy = record[5]
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find_one = True
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agg[model]["items"] += 1
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if accuracy > reference:
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sign = "+"
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agg["better"]["items"] += 1
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agg[model]["better"] += 1
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else:
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sign = "-"
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agg["worse"]["items"] += 1
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agg[model]["worse"] += 1
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item = f"{accuracy:9.7} {sign}"
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line["reference"] = f"{reference:9.7}"
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line[model] = (
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TextColor.GREEN + TextColor.BOLD + item + TextColor.ENDC
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if accuracy == max_accuracy
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else color + item
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)
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if not find_one:
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print(TextColor.FAIL + f"*No results found for {dataset[0]}")
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else:
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color = (
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TextColor.LINE2 if color == TextColor.LINE1 else TextColor.LINE1
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)
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print(report_line(line))
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report_footer(agg)
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dbh.close()
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