# kdemodel properties

 Kernel Density Estimation (KDE)© uses the Ball Tree or KD Tree algorithms for efficient queries, and combines concepts from unsupervised learning, feature engineering, and data modeling. Neighbor-based approaches such as KDE are some of the most popular and useful density estimation techniques. The KDE Modeling and KDE Simulation nodes in SPSS® Modeler expose the core features and commonly used parameters of the KDE library. The nodes are implemented in Python.
Table 1. kdemodel properties
`kdemodel` properties Data type Property description
`bandwidth` double Default is `1`.
`kernel` string The kernel to use: `gaussian`, `tophat`, `epanechnikov`, `exponential`, `linear`, or `cosine`. Default is `gaussian`.
`algorithm` string The tree algorithm to use: `kd_tree`, `ball_tree`, or `auto`. Default is `auto`.
`metric` string The metric to use when calculating distance. For the `kd_tree` algorithm, choose from: `Euclidean`, `Chebyshev`, `Cityblock`, `Minkowski`, `Manhattan`, `Infinity`, `P`, `L2`, or `L1`. For the `ball_tree` algorithm, choose from: `Euclidian`, `Braycurtis`, `Chebyshev`, `Canberra`, `Cityblock`, `Dice`, `Hamming`, `Infinity`, `Jaccard`, `L1`, `L2`, `Minkowski`, `Matching`, `Manhattan`, `P`, `Rogersanimoto`, `Russellrao`, `Sokalmichener`, `Sokalsneath`, or `Kulsinski`. Default is `Euclidean`.
`atol` float The desired absolute tolerance of the result. A larger tolerance will generally lead to faster execution. Default is `0.0`.
`rtol` float The desired relative tolerance of the result. A larger tolerance will generally lead to faster execution. Default is `1E-8`.
`breadthFirst` renamed to `breadth_first` starting with version 18.2.1.1 boolean Set to `True` to use a breadth-first approach. Set to `False` to use a depth-first approach. Default is `True`.
`LeafSize` renamed to `leaf_size` starting with version 18.2.1.1 integer The leaf size of the underlying tree. Default is `40`. Changing this value may significantly impact the performance.
`pValue` double Specify the P Value to use if you're using `Minkowski` for the metric. Default is `1.5`.
`custom_name`
`default_node_name`
`use_HPO`