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Get Started Free →datadrivenconstruction/ml-model-builder
Build ML models for construction predictions. Train and evaluate custom models for cost, duration, and risk prediction.
Passed 17 of 22 test cases with the skill, and 5 of 22 without it.
and 21 more in the full report
12 fixed5 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
What return value does `predict` produce if requested to execute predictions for a non-existent `model_id`?
| Checked | Without skill | With skill |
|---|---|---|
| Returns dictionary containing error key mapped to 'Model not found' | Missed | Passed |
The instructions your model reads when the skill loads.
Construction prediction challenges:
Comprehensive ML model building framework for construction predictions with data preprocessing, model training, evaluation, and export capabilities.
import pandas as pd
import numpy as np
from typing import Dict, Any, List, Optional, Tuple, Callable
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
import json
import math
class PredictionTarget(Enum):
COST = "cost"
DURATION = "duration"
RISK_SCORE = "risk_score"
PRODUCTIVITY = "productivity"
QUALITY = "quality"
class AlgorithmType(Enum):
LINEAR_REGRESSION = "linear_regression"
RIDGE_REGRESSION = "ridge_regression"
KNN = "knn"
DECISION_TREE = "decision_tree"
test cases passed, vs 5 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.