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Ozone

Los Angeles ozone pollution data, 1976


Description

A data frame with 366 observations on 13 variables, each observation is one day

Usage

data(Ozone)

Format

1 Month: 1 = January, ..., 12 = December
2 Day of month
3 Day of week: 1 = Monday, ..., 7 = Sunday
4 Daily maximum one-hour-average ozone reading
5 500 millibar pressure height (m) measured at Vandenberg AFB
6 Wind speed (mph) at Los Angeles International Airport (LAX)
7 Humidity (%) at LAX
8 Temperature (degrees F) measured at Sandburg, CA
9 Temperature (degrees F) measured at El Monte, CA
10 Inversion base height (feet) at LAX
11 Pressure gradient (mm Hg) from LAX to Daggett, CA
12 Inversion base temperature (degrees F) at LAX
13 Visibility (miles) measured at LAX

Details

The problem is to predict the daily maximum one-hour-average ozone reading (V4).

Source

Leo Breiman, Department of Statistics, UC Berkeley. Data used in Leo Breiman and Jerome H. Friedman (1985), Estimating optimal transformations for multiple regression and correlation, JASA, 80, pp. 580-598.

Examples

data(Ozone)
summary(Ozone)

mlbench

Machine Learning Benchmark Problems

v2.1-3
GPL-2
Authors
Friedrich Leisch and Evgenia Dimitriadou.
Initial release
2021-01-21

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