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Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.

2 votes
2 answers
2k views

imputing missing values of finance data

Or is there any way in R to account for missing values and only create ts values for 1443 data points which are present? … R command used: st_ts = ts(stocks[,2], start = c(2010,1), end = c(2015,9), frequency = 365) …
alily's user avatar
  • 616
1 vote
0 answers
398 views

handling dataset if some columns have sparse data

1)if in a dataset 8 columns and of them 3 columns have sparse data[lots of missing values].can anyone tell me what are the general practices followed to transform this data before modelling. I know we …
alily's user avatar
  • 616
2 votes
1 answer
316 views

how to check if model built is valid or outdated for new data

If i have a classification or clustering model built for retail customers till last year.How do i check if my model is still valid to this year's data? We can check accuracy of model to new data but …
alily's user avatar
  • 616
1 vote
0 answers
32 views

timeseries forecasting when datapoints doesn't start at same time period

I have a dataset which has lifecycle information of different products but all the products doesn't start selling in same period or same year/quarter.In this case how should i do time series modelling …
alily's user avatar
  • 616
2 votes
0 answers
936 views

Time series data prediction with neural network model

I have modeled a neural network with 3 input nodes and 2 hidden nodes and 1 output node in R but I am getting forecast accuracy of around 35% only. …
alily's user avatar
  • 616