User: arronar

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arronar150
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Posts by arronar

<prev • 136 results • page 1 of 14 • next >
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Comment: C: subgraph extraction based on the edges weights and graph connectivity
... I see... Sorry for letting this misconception. ...
written 3 months ago by arronar150
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Comment: C: subgraph extraction based on the edges weights and graph connectivity
... What kind of inspection? Are you looking for graphs with a specific number of expanded nodes or anything different? ...
written 3 months ago by arronar150
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Comment: C: subgraph extraction based on the edges weights and graph connectivity
... > One way of approaching the problem of finding a threshold > automatically could be to find the edges that if removed would > disconnect the graph (they are called bridges and I think there's an > algorithm for finding them). Isn't what the fourth paragraph is talking about? Also based ...
written 3 months ago by arronar150
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Comment: C: subgraph extraction based on the edges weights and graph connectivity
... I don't think that the 4th paragraph is referring to thresholding the adjacency matrix. As I understood they propose to apply the threshold to the edge relevance scores. I have already implemented the k-walk algorithm and the results I got are in the form of the dataframe described in the OP. So now ...
written 3 months ago by arronar150
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Comment: C: subgraph extraction based on the edges weights and graph connectivity
... Thank you for your answer but it confused me a little bit. Why did you choose as initial nodes the A,B and C? For some reason, you chose the induced network to be constructed by those nodes. As I understood from the literature,the induced graph should be the result of the whole process. Why choose o ...
written 3 months ago by arronar150
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subgraph extraction based on the edges weights and graph connectivity
... Hi. Given a matrix that describes the edges' and their weights of a connected graph (see below) I want to extract a subgraph based on a threshold value **x** for the edges' weights. In literature, I read that one can search for the **maximal x**, such that the induced subgraph is connected. Since ...
R extraction subgraph weight graph written 3 months ago by arronar150 • updated 3 months ago by ejm32420
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Comment: C: Is sampling for training and testing, necessary in random forest algorithms
... I'm keeping the ones with accuracy >65% and then the best one of them. I'm doing CV 50 times because I realized that each time, models have different accuracy. E.g the first could have 34% accuracy while the second 72%. If I don't use CV will the algorithm keep the best one? ...
written 7 months ago by arronar150
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Is sampling for training and testing, necessary in random forest algorithms
... Hi. I'm trying to apply, random forest algorithm onto microarray results in order to get a list with the most significant predictors. So far I was executing the following pipeline. buildForest <- function (RF.data, storeDir) { acc = numeric() for(i in 1:50){ ...
microarray importance random forest written 7 months ago by arronar150 • updated 7 months ago by Jean-Karim Heriche16k
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Comment: C: Why GSVA returns a matrix with fewer gene-sets?
... Oh. my god. row.names are in lowercase while the gene-sets in uppercase. That is the cause of the problem. ...
written 7 months ago by arronar150
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Comment: C: Why GSVA returns a matrix with fewer gene-sets?
... `> GSC.C2.msigdb` returns : First 50 (out of 4738) gene set names: [1] "KEGG_GLYCOLYSIS..." "KEGG_CITRATE_CY..." "KEGG_PENTOSE_PH..." "KEGG_PENTOSE_AN..." "KEGG_FRUCTOSE_A..." [6] "KEGG_GALACTOSE_..." "KEGG_ASCORBATE_..." "KEGG_FATTY_ACID..." "KEGG_STEROID_BI..." "KEGG_PRIMARY_BI.. ...
written 7 months ago by arronar150

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