Update README.md

README.md

@@ -103,7 +103,7 @@ As the Internet is constantly changing, about two thirds of the original images
 
 ## How was this dataset created?
 
-MapPool has been created by classifying the image embeddings included in [CommonPool](https://huggingface.co/datasets/mlfoundations/datacomp_xlarge) which have been generated by two pre-trained vision transformers (ViTs). The [L/14 model](https://github.com/mlfoundations/open_clip) with more parameters and outputting 768-dimensional embeddings has been considered as it has achieved higher classification accuracies. In this work, different map classifiers (Table 1) from [scikit-learn](https://scikit-learn.org/) with the [Intel Extension](https://intel.github.io/scikit-learn-intelex) have been trained on the embeddings of 1,860 maps and 1,860 non-maps, and has been evaluated on 1,240 maps and 1,240 non-maps ([Schnürer et al. 2021](https://doi.org/10.1080/00087041.2020.1738112)). Only simple classification models have been considered due to their efficiency and as meaningful embeddings have been already created by the vision transformer.
+MapPool has been created by classifying the image embeddings included in [CommonPool](https://huggingface.co/datasets/mlfoundations/datacomp_xlarge) which have been generated by two pre-trained vision transformers (ViTs). The [L/14 model](https://github.com/mlfoundations/open_clip) with more parameters and outputting 768-dimensional embeddings has been considered as it has achieved higher classification accuracies. In this work, different map classifiers (see Table below) from [scikit-learn](https://scikit-learn.org/) with the [Intel Extension](https://intel.github.io/scikit-learn-intelex) have been trained on the embeddings of 1,860 maps and 1,860 non-maps, and has been evaluated on 1,240 maps and 1,240 non-maps ([Schnürer et al. 2021](https://doi.org/10.1080/00087041.2020.1738112)). Only simple classification models have been considered due to their efficiency and as meaningful embeddings have been already created by the vision transformer.
 
 | Model                                                    | Accuracy 
 |----------------------------------------------------------|----------