Think of a classification problem from your own experience and interest (e.g., distinguishing between two types of things/living beings/weather/personality/vehicle/industry/sports/houses/professionals etc.) Collect some real-world data to solve that classification problem. Have at least two classes, two attributes and at least 5 instances per class. Create a dataframe with this data and paste a screenshot of it. Also give a short description of the data (number of instances, number of attributes and the list of attributes and list of classes). The attributes should be numerical. The classification problem should be a new one, but the dataset may contain data that are new (generated by you by any rough measurements) or collected from public domain. Please cite the references/sources from which you collect the data.
Think of a classification problem from your own experience and interest (e.g., distinguishing
between two types of things/living beings/weather/personality/vehicle/industry/sports/houses/professionals etc.) Collect some real-world data to solve that classification problem. Have at least two classes, two attributes and at
least 5 instances per class. Create a dataframe with this data and paste a screenshot of it. Also give a short description of the data (number of instances, number of attributes and the list of attributes and list of classes). The attributes should be numerical. The classification problem should be a new one, but the dataset may contain data that are new (generated by you by any rough measurements) or collected from public domain. Please cite the references/sources from which you collect the data.
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