## Logistic regression
data(colon)
X <- colon$X
y <- colon$y
X.bm <- as.big.matrix(X, backingfile = "")
fit <- biglasso(X.bm, y, penalty = 'lasso', family = "binomial")
coef <- coef(fit, lambda=0.05, drop = TRUE)
coef[which(coef != 0)]
predict(fit, X.bm, type="link", lambda=0.05)[1:10]
predict(fit, X.bm, type="response", lambda=0.05)[1:10]
predict(fit, X.bm, type="class", lambda=0.1)[1:10]
predict(fit, type="vars", lambda=c(0.05, 0.1))
predict(fit, type="nvars", lambda=c(0.05, 0.1))
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