Information

Information about the dataset

The dataset selection was based on the existing issues in the mobile phone market. The saturation of devices makes it difficult for consumers to differentiate quality among models, complicating their purchasing process. Furthermore, the lack of tools to compare the relationship between prices and device components adds to this difficulty.

To address these issues and find a solution, a dataset was chosen that includes a wide range of technical specifications of mobile phones along with their price classification. This dataset will serve as the foundation for training a decision tree model. This model could assist consumers in making more informed decisions when purchasing a mobile phone within their preferred price range, providing a way to classify devices based on their technical characteristics.

In this data:
id: ID
battery_power: Total energy a battery can store in one time measured in mAh
blue: Has bluetooth or not
clock_speed: speed at which microprocessor executes instructions
dual_sim: Has dual sim support or not
fc: Front Camera mega pixels
four_g: Has 4G or not
int_memory: Internal Memory in Gigabytes
m_dep:Mobile Depth in cm
mobile_wt: Weight of mobile phone
n_cores: Number of cores of processor
pc: Primary Camera mega pixels
px_height:Pixel Resolution Height
px_width: Pixel Resolution Width
ram: Random Access Memory in Megabytes
sc_h: Screen Height of mobile in cm
sc_w: Screen Width of mobile in cm
talk_time: longest time that a single battery charge will last when you are
three_g: Has 3G or not
touch_screen: Has touch screen or not
wifi: Has wifi or not