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出租公寓分类数据集

出租公寓分类数据集

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Business Classification, Regression, Clustering

This is a dataset of classified for apartments for rent in USA. ......

数据结构 ? 0M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Collected from Internet 2019-12-28 for an Machine learning task and I want to share this dataset with all who is interested to use it.
    For any questions about the dataset feel free to contact me on fredrick_nilsson '@' yahoo.comthe names, email addresses, institutions, and other contact information of the donors and creators of the data set.


    Data Set Information:

    The dataset contains of 10'000 or 100'000 rows and of 22 columns The data has been cleaned in the way that
    column price and square_feet never is empty but the dataset is saved as it was created.

    Can be used for different machine learning tasks such as clustering, classification and also regression for the squares feet column


    Attribute Information:

    Provide information
    id = unique identifier of apartment
    category = category of classified
    title = title text of apartment
    body = body text of apartment
    amenities = like AC, basketball,cable, gym, internet access, pool, refrigerator etc.
    bathrooms = number of bathrooms
    bedrooms = number of bedrooms
    currency = price in current
    fee = fee
    has_photo = photo of apartment
    pets_allowed = what pets are allowed dogs/cats etc.
    price = rental price of apartment
    price_display = price converted into display for reader
    price_type = price in USD
    square_feet = size of the apartment
    address = where the apartment is located
    cityname = where the apartment is located
    state = where the apartment is located
    latitude = where the apartment is located
    longitude = where the apartment is located
    source = origin of classified
    time = when classified was created
    bout each attribute in your data set.


    Relevant Papers:

    Provide references to papers that have cited this data set in the past (if any).



    Citation Request:

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