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Commit 10cd74d4 by Rebecca Merrett
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Changing directory example and multi-line comments

parent 814cc5fb
Showing with 34 additions and 34 deletions
Time Series/r_time_series_example.R
...@@ -6,7 +6,7 @@ library(tseries) ...@@ -6,7 +6,7 @@ library(tseries)
# Set your working directory to where your script and # Set your working directory to where your script and
# data files sit on your local computer # data files sit on your local computer
setwd("C:\\Users\\Rebecca\\Desktop\\time_series") setwd("C:\\Your\\Directory\\Here")
# Read csv file of train dataset as a univariate # Read csv file of train dataset as a univariate
# (single variable) series, with datetime # (single variable) series, with datetime
...@@ -145,36 +145,36 @@ mean_absolute_error ...@@ -145,36 +145,36 @@ mean_absolute_error
# is stationary # is stationary
adf.test(hourly_sentiment_series_diff2) adf.test(hourly_sentiment_series_diff2)
#-Need to better transform these data: "-Need to better transform these data:
# You could look at stabilizing the variance by applying You could look at stabilizing the variance by applying
# the cube root for neg and pos values and then the cube root for neg and pos values and then
# difference the data difference the data
#-You might compare models with different AR and MA terms -You might compare models with different AR and MA terms
#-This is a very small sample size of 24 timestamps, -This is a very small sample size of 24 timestamps,
# so might not have enough to spare for a holdout set so might not have enough to spare for a holdout set
# To get more use out of your data for training, rolling over time To get more use out of your data for training, rolling over time
# series or timestamps at a time for different holdout sets series or timestamps at a time for different holdout sets
# allows for training on more timestamps; doesn't stop the model from allows for training on more timestamps; doesn't stop the model from
# capturing the last chunk of timestamps stored in a single holdout set capturing the last chunk of timestamps stored in a single holdout set
#-The data only looks at 24 hours in one day -The data only looks at 24 hours in one day
# Would we start to capture more of a trend in hourly sentiment if we Would we start to capture more of a trend in hourly sentiment if we
# collected data over several days? collected data over several days?
# How would you go about collecting more data? How would you go about collecting more data?
# Take on the challenge and further improve this model: Take on the challenge and further improve this model:
# You have been given a head start, now take this example You have been given a head start, now take this example
# and improve on it! and improve on it!
# To study time series further: To study time series further:
#-Look at model diagnostics -Look at model diagnostics
#-Use AIC to search best model parameters -Use AIC to search best model parameters
#-Handle any datetime data issues -Handle any datetime data issues
#-Try other modeling techniques -Try other modeling techniques
# Learn more during a short, intense bootcamp: Learn more during a short, intense bootcamp:
# Time Series to be introduced in Data Science Dojo's Time Series to be introduced in Data Science Dojo's
# post bootcamp material post bootcamp material
# Data Science Dojo's bootcamp also covers some other key Data Science Dojo's bootcamp also covers some other key
# machine learning algorithms and techniques and takes you through machine learning algorithms and techniques and takes you through
# the critical thinking process behind many data science tasks the critical thinking process behind many data science tasks
# Check out the curriculum: https://datasciencedojo.com/bootcamp/curriculum/ Check out the curriculum: https://datasciencedojo.com/bootcamp/curriculum/"
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