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I am new to box plots and I am trying to understand it. Consider the following figures :
According to my understanding, outliers will exist after the max. line and before the min. line. So according to the above figures, we can see that outliers exist ( except for the EXT_Source 2 and EXT_Source 3 attributes) , which are labelled as black small circles after the max. value of each variable, am I right ??
Your interpretation of a boxplot is correct.
But outlier definition in general terms is subjective... to simplify the idea let´s consider just the top outliers (but probably you should consider the bottom ones too): you could use the 1% top values to consider them outliers, or do as the boxplot does and take the ones that exceed Q3 + 1.5 IQR, or do as Tukey and consider Q3 + 3IQR.
If you use R, you could leverage this chapter of the Data Science Live Book
