X-Git-Url: https://git.auder.net/rpsls.js?a=blobdiff_plain;f=pkg%2FR%2FF_Neighbors.R;h=27cd23a7c31a5ad5691434568afee26c96499410;hb=9003747badc4416d68cab45ff17de3ecea327942;hp=d889a34ce64b82c51889a5a81322a1a7dec25b2c;hpb=ee8b1b4e3c13f8dcf13a2c8da6a3bef1520c8252;p=talweg.git

diff --git a/pkg/R/F_Neighbors.R b/pkg/R/F_Neighbors.R
index d889a34..27cd23a 100644
--- a/pkg/R/F_Neighbors.R
+++ b/pkg/R/F_Neighbors.R
@@ -30,12 +30,8 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					fdays, today, horizon, list(...)$h_window, kernel, simtype, TRUE) )
 			}
 
-			# Indices of similar days for cross-validation; TODO: 45 = magic number
-			sdays = getSimilarDaysIndices(today, data, limit=45, same_season=FALSE)
-
-			cv_days = intersect(fdays,sdays)
-			# Limit to 20 most recent matching days (TODO: 20 == magic number)
-			cv_days = sort(cv_days,decreasing=TRUE)[1:min(20,length(cv_days))]
+			# Indices of similar days for cross-validation; TODO: 20 = magic number
+			cv_days = getSimilarDaysIndices(today, data, limit=20, same_season=FALSE, days_in=fdays)
 
 			# Function to optimize h : h |--> sum of prediction errors on last 45 "similar" days
 			errorOnLastNdays = function(h, kernel, simtype)
@@ -60,12 +56,12 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 			if (simtype != "endo")
 			{
 				h_best_exo = optimize(
-					errorOnLastNdays, c(0,10), kernel=kernel, simtype="exo")$minimum
+					errorOnLastNdays, c(0,7), kernel=kernel, simtype="exo")$minimum
 			}
 			if (simtype != "exo")
 			{
 				h_best_endo = optimize(
-					errorOnLastNdays, c(0,10), kernel=kernel, simtype="endo")$minimum
+					errorOnLastNdays, c(0,7), kernel=kernel, simtype="endo")$minimum
 			}
 
 			if (simtype == "endo")
@@ -172,11 +168,11 @@ NeighborsForecaster = R6::R6Class("NeighborsForecaster",
 					simils_endo
 				else #mix
 					simils_endo * simils_exo
+			similarities = similarities / sum(similarities)
 
 			prediction = rep(0, horizon)
 			for (i in seq_along(fdays))
 				prediction = prediction + similarities[i] * data$getCenteredSerie(fdays[i]+1)[1:horizon]
-			prediction = prediction / sum(similarities, na.rm=TRUE)
 
 			if (final_call)
 			{