1. Objective: We want to predict median home value in a region based on housing value related predictor fields.

2. License: Free to use.

3. Data Source: https://archive.ics.uci.edu/ml/datasets/Housing

4. DataSet Info: Housing values in suburbs of Boston where we have 506 records.

5. Field Meanings:
	A. crime_rate: Per capita crime rate by town
	B. land_zone: Proportion of residential land zoned for lots over 25,000 sq.ft.
	C. business_acres: Proportion of non-retail business acres per town
	D. charles_river_adjacency: Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)
	E. nitric_oxide_concentration: Nitric oxides concentration (parts per 10 million)
	F. avg_rooms_per_dwelling: Average number of rooms per dwelling
	G. units_prior_1940: Proportion of owner-occupied units built prior to 1940
	H. distance_to_employment_center: Weighted distances to five Boston employment centres
	I. highway_accessibility_index: Index of accessibility to radial highways
	J. property_tax_rate: Full-value property-tax rate per $10,000
	K. pupil_teacher_ratio: Pupil-teacher ratio by town
	L. median_house_value: Median value of owner-occupied homes in $1000's

6. Parameter Selection:
	A. Dashboard Usage: Predict Numerical Fields for business analyst role.
	Settings:
	   1) Search command: | inputlookup housing.csv
	   2) Field to predict: median_house_value
	   3) Fields to use for predicting: crime_rate, land_zone, nitric_oxide_concentration, avg_rooms_per_dwelling, units_prior_1940, distance_to_employment_center, highway_accessibility_index, property_tax_rate, pupil_teacher_ratio


  B. Dashboard: Cluster Numeric Fields
        Settings:
    0) Search: | inputlookup housing.csv
    1) Model name: N/A
    2) Fields to preprocess: avg_rooms_per_dwelling, business_acres, crime_rate, distance_to_employment_center, highway_accessibility_index, land_zone, median_house_value, nitric_oxide_concentration, property_tax_rate, pupil_teacher_ratio, units_prior_1940
    3) Apply StandardScaler
    4) Apply PCA to reduce to 3 fields
    5) Algorithm: DBSCAN
    6) Fields to use: PC_1, PC_2, PC_3
    7) eps: 0.96