Forum Discussion
predictive analytics
what do you mean by predictive analytics in this context? Do you have some R scripts that you're looking to run and output the data of, or create some visuals off the back of that?
Without some more explicit information it's unlikely anyone on this board will be able to help you.
George.
created time is when the tickets are created. and count id is a measure of tickets(count of tickets) below is the code i have exceuted
library(forecast)
data2<-data.frame(dataset)
# group searches by date
dataset <- aggregate(Count_Id ~ Created_Time, data = data2, FUN= sum)
summary(dataset)
# create a time series based on day of week
ts <- ts(data2$Count_Id, frequency=4)
# pull out the seasonal, trend, and irregular components from the time series (train the forecast model)
decom <- stl(ts, s.window = "periodic")
# predict the next 7 days of searches
pred <- forecast(decom, h = 3)
# plot the predicted searches
plot(pred)
and finally i got the graph, but i am not understanding what the graph is exactly saying
is there any possibility to getany graph model instead of this model.
can you please explain me what graph is saying
Hi kalpanaV,
For forecast package in R, it uses ARIMA model to estimate the futher, so it need to time series. You can also use other model like linear fitting to estimate the further data, which needs to create the function by yourself.
Best Regards,
Angeliacan you please tell me wat function i need to create?
I have the data for july month1 to 31 (data is about tickets).
i want to predict the no of tickets for next month.
below are the code which i executed.
i cretaed a measure called count_id. created_time is the field(date)
library(forecast)
data2<-data.frame(dataset)
# group searches by date
dataset <- aggregate(Count_Id ~Created_Time , data = data2, FUN= sum)
summary(dataset)
# create a time series based on day of week
ts <- ts(data2$Count_Id, frequency=4)# pull out the seasonal, trend, and irregular components from the time series (train the forecast model)
decom <- stl(ts, s.window = "periodic")# predict the next 7 days of searches
pred <- forecast(decom, h = 3)# plot the predicted searches
plot(pred)
