Limits on rows - Truncated data set - Missing - Non-missing data
Hello,
I am a newbie. Downloaded RapidMiner Free Studio (my understanding is it comes with one month of studio Enterprise) and signed up for RapidMiner GO on Saturday (April 3rd). Watched all the Academy videos (if you are going to send me there
). Started playing around and I got to several problems.
DIsclaimer - At the moment I am evaluating head-to-head performance of RapidMiner, Weka and Orange. Weka and Orange are free, RM Go cost at 10$ a month is comparable.
My understanding is that if file <50MB, <500 attributes file should be good to go on RapidMiner Go.
So, I have a file of size <50MB, 11 attributes and 542 919 rows. No missing data in the dataset - not a single one.
I 've run a classification on it, but unfortunately, it got truncated down to 120 000 rows.
I have not gotten any notification in between.
I also did some predictive modeling and I get a lot of MISSING data (especially obvious when I predict on a testing set).
So far - this was GO.
For the first month of Free RM Studio, I get Enterprise Studio where there is no limit on anything ( in theory). My computer has 16GB of RAM (if somebody is to ask - not bad, not great either).
When I execute the same Modeling with AutoModel in Studio (I have Free Educational License with would come with a month of Enterprise Studio) I get even more truncated results - It all stops at 100 000 rows.
Even worse - there is not a single missing point in the dataset, but there are missing in the prediction.
So, my questions are: is the data truncated in Go? Is data truncated in Studio? Why Missing Values if there is not a single missing or NA cell in the dataset? How can I overcome this if I am to use RM in the future?
Thank you so much,
Radostina
I am a newbie. Downloaded RapidMiner Free Studio (my understanding is it comes with one month of studio Enterprise) and signed up for RapidMiner GO on Saturday (April 3rd). Watched all the Academy videos (if you are going to send me there
). Started playing around and I got to several problems. DIsclaimer - At the moment I am evaluating head-to-head performance of RapidMiner, Weka and Orange. Weka and Orange are free, RM Go cost at 10$ a month is comparable.
My understanding is that if file <50MB, <500 attributes file should be good to go on RapidMiner Go.
So, I have a file of size <50MB, 11 attributes and 542 919 rows. No missing data in the dataset - not a single one.
I 've run a classification on it, but unfortunately, it got truncated down to 120 000 rows.
I have not gotten any notification in between.
I also did some predictive modeling and I get a lot of MISSING data (especially obvious when I predict on a testing set).
So far - this was GO.
For the first month of Free RM Studio, I get Enterprise Studio where there is no limit on anything ( in theory). My computer has 16GB of RAM (if somebody is to ask - not bad, not great either).
When I execute the same Modeling with AutoModel in Studio (I have Free Educational License with would come with a month of Enterprise Studio) I get even more truncated results - It all stops at 100 000 rows.
Even worse - there is not a single missing point in the dataset, but there are missing in the prediction.
So, my questions are: is the data truncated in Go? Is data truncated in Studio? Why Missing Values if there is not a single missing or NA cell in the dataset? How can I overcome this if I am to use RM in the future?
Thank you so much,
Radostina