
AI Blueprints
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Perhaps the simplest trend is the linear trend. Naturally, we would only attempt to find such a trend on serial data, such as data ordered by time. For this example, we will use the daily frequency of email messages on the R-help mailing list (https://stat.ethz.ch/mailman/listinfo/r-help), an email list for users seeking help with the R programming language. The mailing list archive includes every message and the time it was sent. We wish to find a daily linear trend of message frequency, as opposed to hourly, minutely, monthly, yearly, and so on. We must decide the unit of frequency before applying trend or anomaly analysis, as the count of messages per day may be strongly linear while the count per hour may be non-linear and highly seasonal (that is, some hours are consistently higher than others), thus dramatically changing the technique that should be applied for the analysis.
Before loading the dataset, we must import pandas
for loading the CSV file, sklearn...