Machine Learning: Diamond Price Prediction in Forex
Data Set Information: A dataset containing the prices and other features of almost 54,000 diamonds.
Features description Number of Attributes: 10 (9 predictive features, 1 target)
Feature Information: A data frame with 53,940 rows and 10 variables:
price: price in US dollars ($326–$18,823) (target)
carat: weight of the diamond (0.2–5.01)
cut: quality of the cut (Fair, Good, Very Good, Premium, Ideal)
color: diamond colour, from J (worst) to D (best)
clarity: a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))
x: length in mm (0–10.74)
y: width in mm (0–58.9)
z: depth in mm (0–31.8)
depth: total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43–79)
table: width of top of diamond relative to widest point (43–95)