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Boston Housing
🏠· Target: 82% accuracy
Data Preview
Features
Scaling
Train
Dataset Overview
506 rows19
TOTAL COLUMNS
16
NUMERIC FEATURES
0
MISSING COLUMNS
7
OUTLIER COLUMNS
Data Quality Issues Detected
• CRIM: contains outliers
• RM: contains outliers
• LSTAT: contains outliers
• ZN: contains outliers
• B: contains outliers
• Tax per Room: contains outliers
• LSTAT Squared: contains outliers
| Column | Type | Sample Values | Distribution | Missing | Outliers | Importance |
|---|---|---|---|---|---|---|
MEDV TARGETTarget: Median home value ($1000s) | Target | 2421.634.7 | — | None | Yes | |
CRIM Per capita crime rate by town | Numeric | 0.0060.0270.027 | μ=3.6 σ=8.6 | None | Yes | 66% |
RM Average rooms per dwelling | Numeric | 6.576.427.18 | μ=6.28 σ=0.7 | None | Yes | 82% |
LSTAT % lower status of population | Numeric | 4.989.144.03 | μ=12.65 σ=7.14 | None | Yes | 88% |
DIS Weighted distance to employment centres | Numeric | 4.094.976.06 | μ=3.8 σ=2.1 | None | No | 59% |
TAX Full-value property-tax rate per $10k | Numeric | 296242242 | μ=408 σ=169 | None | No | 48% |
NOX Nitric oxide concentration (ppm) | Numeric | 0.5380.4690.469 | μ=0.555 σ=0.116 | None | No | 53% |
PTRATIO Pupil-teacher ratio by town | Numeric | 15.317.817.8 | μ=18.5 σ=2.16 | None | No | 41% |
ZN Proportion of residential land (large lots) | Numeric | 1800 | μ=11.4 σ=23.3 | None | Yes | 22% |
INDUS Proportion of non-retail business acres | Numeric | 2.317.077.07 | μ=11.1 σ=6.8 | None | No | 48% |
CHAS Charles River dummy variable | Binary | 000 | — | None | No | 15% |
AGE Proportion of owner-occupied units built prior to 1940 | Numeric | 65.278.961.1 | μ=68.6 σ=28.1 | None | No | 45% |
RAD Index of accessibility to radial highways | Numeric | 122 | μ=9.5 σ=8.7 | None | No | 38% |
B Proportion of Black population | Numeric | 396.9392.8394.6 | μ=356.6 σ=91.2 | None | Yes | 25% |
Geo Noise 1 Irrelevant geographic metric | Numeric | 1.24.52.3 | μ=3 σ=1.5 | None | No | 1% |
Geo Noise 2 Irrelevant geographic metric | Numeric | 442255 | μ=33 σ=15 | None | No | 2% |
Tax per Room TAX divided by RM | Numeric | 45.137.633.7 | μ=66.8 σ=31.5 | None | Yes | 42% |
Has River Access Derived from CHAS | Categorical | YesNo | — | None | No | 12% |
LSTAT Squared Squared LSTAT (non-linear feature) | Numeric | 24.883.516.2 | μ=211 σ=236 | None | Yes | 85% |
💡 Review the data carefully — understanding your features helps you make better preprocessing choices.
── PIPELINE SCORE ────
66/100
Accuracy modifier: ×1.02
Features
86
Scaling
65
Outliers
30
Architect
75
⚡ Remove low-importance features (<25%) to reduce noise.
⚡ Some features are highly skewed — try Log or Sqrt normalization.
⚡ You have outlier columns — consider clipping or imputing them.
Step 1 of 3
Score: 66/100