| from sklearn.datasets import make_classification | |
| from sklearn.linear_model import RandomizedLogisticRegression | |
| import pandas as pd | |
| clf = RandomizedLogisticRegression(sample_fraction = .75, n_resampling = 3, normalize = False) | |
| X, y = make_classification(n_samples=10, | |
| n_features=3, | |
| n_informative=2, | |
| n_redundant=0, |
| curl -X PURGE |
one has to get a new fork from dmlc/xgboost like this one
because of the use of submodules, devtools doesn't work anymore with installing the R-packages. One has to remove the submodules in the following manner:
bring back the necessary customizations that we've made here
test the new repo with avant-analytics and run("demo_xgb_R")
| for i in `ls .`; do; | |
| md5 $i | cut -d' ' -f4 > $i.md5 | |
| done; | |
| lapply(list.files(pattern = "md5$"), readLines) |
| body(mod$predict_fn) <- edit(body(mod$predict_fn)) |
| v <- sample(1:1000, 50000000, replace = T) | |
| df <- data.frame(id = v) | |
| # split(df, df$id)) is SLOW because it's O(n^2) | |
| # sort(df$id) is FAST because it's O(n ln n) | |
| sid <- sort(df$id) | |
| rle(sid) -> rlesid # Fast because O(n) | |
| tally <- 1 | |
| values <- numeric(length(rlesid$lengths)); indices <- numeric(length(rlesid$lengths)) | |
| for (i in seq_along(indices)) { | |
| indices[i] <- tally |
| sudo apt-get install -y openjdk-7-jre-headless | |
| sudo R CMD javareconf |
| name: yourpkg | |
| version: 0.1.0 | |
| remote: local | |
| dir: /your/pkg | |
| add this to your lockfile and comment out the part that installs from github |
| a|b|c - means contains the strings "a" or "b" or "c" | |
| ^(a|b|c)$ - means IS the string 'a' or 'b' or 'c' same as: %in% c('a','b','c') | |
| ^(a|b|c) - means begins with 'a' or 'b' or 'c' | |
| (a|b|c)$ - means ends with 'a' or 'b' or 'c' | |
| ^[a-zA-Z0-9]*$ - means IS the string contains only a-z, A-Z or 0-9 |
| :%s/tu_final_prediction_data/env$data/g #massive string replacement |