La clave del éxito: cómo aprender de Malcolm Gladwell y sus epidemias sociales
sagim is not designed to be a classifier. its main goal is to extract information from pdfs. it is an unsupervised learning tool. the sagim will be able to: extract the main tables and list of figures
extract chapter name, chapter number, chapter topics, etc
everything else is optional.
you will be able to specify the level of detail you want in extracted information by setting the parameters of the model. some of the parameters of the model are very specific to the extraction process. you will be able to set them using a gui, in the settings menu of the latex cmd.
the eclaclavedelexitomalcolmgladwellpdf function converts an area to an eclaclavedelexitomalcolmgladwellpdf area, with the distinction that the area is of bounding boxes, meaning that the fractional part of each corner is taken into account. it returns a list of pairs of real numbers, each pair corresponding to the upper left-hand corner of the bounding box relative to the area. the first number of each pair is the x-coordinate, the second is the y-coordinate. because it returns a list, the function can be used in a list of areas.
the laccentar function returns a raster of the same size as the source raster. it sets to 1 all the pixels on the borders of the source raster, and all the pixels on the boundaries of the laccentar raster, whereas it sets to 0 all the rest of the pixels.
the lclustering function returns the lowest-level cluster, according to the cluster number used by the lclustering command, for the given set of layer areas. this function is intended to provide a fast implementation for lclustering when the number of groups is low. it should be used instead of the other functions provided by sp for low-number clustering.