Description Usage Arguments Value Examples
Collapses the multi-label predictions across sets of classifier chains and iterations into a single set of predictions, either binary or probabilistic.
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object |
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A matrix of predictions.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | x <- movies_train[, -(1:3)]
y <- movies_train[, 1:3]
model_glm <- ecc(x, y, m = 1, .f = glm.fit, family = binomial(link = "logit"))
predictions_glm <- predict(model_glm, movies_test[, -(1:3)],
.f = function(glm_fit, newdata) {
# Credit for writing the prediction function that works
# with objects created through glm.fit goes to Thomas Lumley
eta <- as.matrix(newdata) %*% glm_fit$coef
output <- glm_fit$family$linkinv(eta)
colnames(output) <- "1"
return(output)
}, n.iters = 10, burn.in = 0, thin = 1)
summary(predictions_glm, movies_test[, 1:3])
## Not run:
model_c50 <- ecc(x, y, .f = C50::C5.0)
predictions_c50 <- predict(model_c50, movies_test[, -(1:3)],
n.iters = 10, burn.in = 0, thin = 1,
.f = C50::predict.C5.0, type = "prob")
summary(predictions_c50, movies_test[, 1:3])
model_rf <- ecc(x, y, .f = randomForest::randomForest)
predictions_rf <- predict(model_rf, movies_test[, -(1:3)],
n.iters = 10, burn.in = 0, thin = 1,
.f = function(rF, newdata){
randomForest:::predict.randomForest(rF, newdata, type = "prob")
})
summary(predictions_rf, movies_test[, 1:3])
## End(Not run)
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