User: arronar
arronar • 50
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Posts by arronar
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... Hello out there.
I was thinking to apply decision tree algorithm on my microarrays data as a supervised method for learning but all examples found out there are using binary categorical variable. Either alive or dead, either red or green, either sun or rain and so on. That realization made me wonde ...
written 8 weeks ago by
arronar • 50
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127
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... If i understood after the colMeans() I'm going to have a new matrix with 6 (treatments) x 920 (genes). Isn't this matrix too small to get training and test data from it ? To train the kNN i need at least one occasion from each treatment. That means that I will use all 6 rows to train the algorithm. ...
written 8 weeks ago by
arronar • 50
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127
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... To be honest I didn't exactly understood what you just said :-) ...
written 8 weeks ago by
arronar • 50
0
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1
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127
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... Bad news. It has 80% error with k=31. Here is the image.
![enter image description here][1]
Also, Ii just see a mistake that I made in my initial post. I didn't mean 30-35%. I meant 50-55% error rate.
30-35% I can get only if i delete some of the replication treatments that has low correlation in ...
written 8 weeks ago by
arronar • 50
0
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1
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127
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... Hi theobroma22
My Initial matrix is 920x60. I used the 70% of this as training set and the rest 30% as test set. I did this 100 different times using sample() function and for k number 1:20. While the error rate i counted as below:
for(y in 1:100){
train_set = sample(...)
t ...
written 8 weeks ago by
arronar • 50
0
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1
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127
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... Hi.
I'm analyzing a microarray dataset that is consisted by 920 variables (genes) and 6 samples (treatments) with replications (10 replications per sample)
I ran a kNN classification on those data with knn() function in R for 100 different samples each time and I got an error rate about 30-35%. S ...
written 8 weeks ago by
arronar • 50
0
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1
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139
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1
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... Hello.
I have a bunch of migroarray data in an array and i wanna run the kNN algorithm on them. So for simplicity let's say that I have for 100 genes in 4 different treatments a table with expression levels.
| Gene name | Treat 1 | Treat 2 | Treat 3 | Treat 4|
----------------------------- ...
written 9 weeks ago by
arronar • 50
• updated
9 weeks ago by
Jean-Karim Heriche ♦ 12k
0
votes
1
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199
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1
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... Thank you very much. Seems that it works. ...
written 11 weeks ago by
arronar • 50
2
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1
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199
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1
answer
... Hello.
I'm running a PCA analysis on R with 62 variables and when creating the biplot some vectors are getting on top of others and i cannot read their labels (see pic). Is there any way to make them more readable.
![enter image description here][1]
I used the factoextra package to plot it by ru ...
written 11 weeks ago by
arronar • 50
• updated
11 days ago by
Alex Reynolds ♦ 19k
0
votes
2
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240
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2
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... The initial microarray data was expression values and normalized them with quantile method. Then i run on them a dunnet's test to get the most significant deregulated (differentially expressed) genes. Let's say that for each treatment i got the following DE genes
deregulated_treat1 = c( 1, 2, 3 ...
written 12 weeks ago by
arronar • 50
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