diff --git a/README.Rmd b/README.Rmd
index c9cb899..4c93da3 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -52,12 +52,10 @@ output: github_document
News of this version (`r packageVersion('IBCF.MTME')`)
- * `MSEP` was changed to `MAAPE`.
- * `print` function was added.
- * `ORCID` was added to the authors of the package.
- * `IBCF.Years()` now has `colID` parameter to select the identifiers of the observations.
- * Fixed a bug caused by the sequence in a for cycle.
-
+
+ * Fixed issue [2] with the predictions in the pm$Data.Obs_Pred output, thanks to @melissa-garcia to report it.
+ * Fixed issue with the Cross-validation with two or more traits to use as testing.
+
See the last updates in [NEWS](NEWS.md).
@@ -85,7 +83,7 @@ devtools::install_github('frahik/IBCF.MTME')
If you want to use the stable version of `IBCF.MTME` package, install it from CRAN.
```{r, eval=FALSE}
-install.packages('BGGE')
+install.packages('IBCF.MTME')
```
@@ -141,10 +139,24 @@ pm <- IBCF(CrossV)
Show some results
+All the predictive model printed output:
+
```{r}
-summary(pm)
+pm
+```
+
+Predictions and observed data in tidy format
+```{r}
+head(pm$predictions_Summary, 6)
+```
+
+Predictions and observed data in matrix format
+```{r}
+head(pm$Data.Obs_Pred, 5)
```
+Some plots
+
```{r}
par(mai = c(2, 1, 1, 1))
plot(pm, select = 'Pearson')
diff --git a/README.md b/README.md
index e1c2268..98a7be0 100644
--- a/README.md
+++ b/README.md
@@ -14,7 +14,7 @@ Development version 1.4.2.
-\[Last README update: 2018-11-13\]
+\[Last README update: 2018-11-22\]
@@ -67,12 +67,10 @@ News of this version (1.4.2)
- - `MSEP` was changed to `MAAPE`.
- - `print` function was added.
- - `ORCID` was added to the authors of the package.
- - `IBCF.Years()` now has `colID` parameter to select the identifiers
- of the observations.
- - Fixed a bug caused by the sequence in a for cycle.
+ - Fixed issue \[2\] with the predictions in the pm$Data.Obs\_Pred
+ output, thanks to @melissa-garcia to report it.
+ - Fixed issue with the Cross-validation with two or more traits to use
+ as testing.
See the last updates in [NEWS](NEWS.md).
@@ -107,7 +105,7 @@ If you want to use the stable version of `IBCF.MTME` package, install it
from CRAN.
``` r
-install.packages('BGGE')
+install.packages('IBCF.MTME')
```
@@ -186,28 +184,78 @@ Show some results
+All the predictive model printed output:
+
``` r
-summary(pm)
+pm
+```
+
+ ## Item Based Collaborative Filtering Model:
+ ## Fitted with 10 random partitions
+ ## Runtime: 18.25 seconds
+ ##
+ ## Some predicted values:
+ ## [1] -0.9554 -0.2731 -0.5007 -0.0909 -0.0501 -0.2599 -0.3494
+ ## [8] 0.0913 -0.0215 -0.4023 -0.8106 0.5702 0.4918 -1.5810
+ ## [15] -0.1540 -0.8060 -0.6665 -0.0671 -0.1934 -0.3210
+ ##
+ ## Predictive capacity of the model:
+ ## Environment Trait Pearson SE_Pearson MAAPE SE_MAAPE
+ ## 1 Env1 -0.131 0.024 0.931 0.011
+ ## 2 Env2 0.686 0.010 0.674 0.012
+ ## 3 Env3 0.612 0.017 0.682 0.007
+ ## 4 Env4 0.307 0.027 0.762 0.011
+ ##
+ ## Use str() function to found more datailed information.
+
+Predictions and observed data in tidy format
+
+``` r
+head(pm$predictions_Summary, 6)
+```
+
+ ## Position Partition Environment Trait Observed Predicted
+ ## 1 1 1 Env1 1.6716 -0.9554
+ ## 2 14 1 Env1 0.3160 -0.2731
+ ## 3 25 1 Env1 -1.1272 -0.5007
+ ## 4 26 1 Env1 -0.4852 -0.0909
+ ## 5 28 1 Env1 2.5940 -0.0501
+ ## 6 30 1 Env1 -0.5190 -0.2599
+
+Predictions and observed data in matrix
+ format
+
+``` r
+head(pm$Data.Obs_Pred, 5)
```
- ## Environment Trait Pearson SE_Pearson MAAPE SE_MAAPE
- ## 1 Env1 -0.1307 0.0243 0.9312 0.0114
- ## 2 Env2 0.6859 0.0097 0.6737 0.0119
- ## 3 Env3 0.6116 0.0173 0.6823 0.0068
- ## 4 Env4 0.3068 0.0270 0.7623 0.0112
+ ## ID X_Env1.1 X_Env2.1 X_Env3.1 X_Env4.1 X_Env1 X_Env2
+ ## 1 1 1.6716295 -1.72746986 -1.8902848 0.0509159 -0.9894943 -0.8744692
+ ## 2 2 -0.2527028 0.40952243 0.3093855 -1.7387588 -0.5478389 -0.4165869
+ ## 3 3 0.3418151 -0.64862633 -0.7995592 -1.0535691 -0.8596543 -0.6766007
+ ## 4 4 0.7854395 0.09394919 0.5704677 0.5517574 0.4040118 0.5769577
+ ## 5 5 0.9983176 -0.28248062 1.6186819 -0.1142848 0.3243855 1.0403187
+ ## X_Env3 X_Env4
+ ## 1 -0.635018256 -0.5894103
+ ## 2 -0.370835578 0.1360170
+ ## 3 NaN -0.3162934
+ ## 4 0.347986885 0.5066996
+ ## 5 0.001053535 0.7813698
+
+Some plots
``` r
par(mai = c(2, 1, 1, 1))
plot(pm, select = 'Pearson')
```
-
+
``` r
plot(pm, select = 'MAAPE')
```
-
+
@@ -292,13 +340,13 @@ par(mai = c(2, 1, 1, 1))
barplot(pm, las = 2)
```
-
+
``` r
barplot(pm, select = 'MAAPE', las = 2)
```
-
+
@@ -371,17 +419,16 @@ citation('IBCF.MTME')
## Abelardo Montesinos-Lopez and Jose Crossa (2018). IBCF.MTME:
## Item Based Collaborative Filtering for Multi-Trait and
## Multi-Environment Data. R package version 1.4-2.
- ## https://CRAN.R-project.org/package=IBCF.MTME
+ ## https://github.com/frahik/IBCF.MTME
##
## A BibTeX entry for LaTeX users is
##
## @Manual{,
- ## title = {IBCF.MTME: Item Based Collaborative Filtering for Multi-Trait and
- ## Multi-Environment Data},
+ ## title = {IBCF.MTME: Item Based Collaborative Filtering for Multi-Trait and Multi-Environment Data},
## author = {Francisco Javier Luna-Vazquez and Osval Antonio Montesinos-Lopez and Abelardo Montesinos-Lopez and Jose Crossa},
## year = {2018},
## note = {R package version 1.4-2},
- ## url = {https://CRAN.R-project.org/package=IBCF.MTME},
+ ## url = {https://github.com/frahik/IBCF.MTME},
## }
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