Remove need for num_features before fitting - #301
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MoritzWillmann merged 152 commits intoAug 20, 2025
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August 14, 2024 16:55
…d quantum kernel and the Support Vector HLM's
- Extract initialization logic for the FidelityKernel and ProjectedQuantumKernel into a new method "initialize_kernel", which is called within the fit methods of the high-level classes. - Separate the initialization logic for QSVR and QSVC into their own "initialize_kernel" methods, which also invoke the underlying "initialize_kernel" methods of the Fidelity or Projected Kernel.
…other kernel classes
make sure the kernel is fully initialised in the evaluate method before evaluating it. This is necessary to deal with kernel cloning in some cases.
…tures for the QNN classes
this is no longer supported since the constructors have changed and the underlying `LayeredPQC` gets not build in the `__init__` directly
…ans/squlearn into remove_num_features
…uantum framework specific circuit in the init of the `LowLevelQNN`
MoritzWillmann
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Looks good now, LGTM
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Changes Made
1. Delayed Initialization of High-Level Methods
num_featuresparameter is no longer required during the instantiation of high-level methods.num_featuresis not provided, the complete initialization of the high-level method is postponed until thefitmethod is called, allowing the actual number of features to be known.num_featuresis provided during instantiation, the high-level method will be fully initialized immediately.2. New
num_encoding_slotsProperty forEncodingCircuitnum_encoding_slotshas been introduced for eachEncodingCircuit, which calculates the number of encoding slots individually.get_circuitmethod, there is now a check to ensure that the number of provided features matches the number of available encoding slots.EncodingSlotsMismatchErroris raised.closes #266, #292