Drop binarization algorithm support (#2556)

### Changes

- Dropped `binarization` algorithm support (as deprecated before);

### Reason for changes

- Actual state of the algorithms list;

### Related tickets

- 133129

Author: nikita-malininn

README.md

@@ -42,7 +42,6 @@ learning frameworks.
 | :--- | :---: | :---: |
 |[Quantization Aware Training](./docs/compression_algorithms/Quantization.md) | Supported | Supported |
 |[Mixed-Precision Quantization](./docs/compression_algorithms/Quantization.md#mixed-precision-quantization) | Supported | Not supported |
-|[Binarization](./docs/compression_algorithms/Binarization.md) | Supported | Not supported |
 |[Sparsity](./docs/compression_algorithms/Sparsity.md) | Supported | Supported |
 |[Filter pruning](./docs/compression_algorithms/Pruning.md) | Supported | Supported |
 |[Movement pruning](./nncf/experimental/torch/sparsity/movement/MovementSparsity.md) | Experimental | Not supported |

docs/Algorithms.md

@@ -12,9 +12,6 @@ Each compression method receives its own hyperparameters that are organized as a
   - Automatic bitwidth assignment based on HAWQ
   - Automatic quantization parameter selection and activation quantizer setup based on HW config preset
   - Automatic bitwidth assignment mode AutoQ, based on HAQ, a Deep Reinforcement Learning algorithm to select best mixed precision given quality metric and HW type.
-- [Binarization](./compression_algorithms/Binarization.md)
-  - XNOR, DoReFa weight binarization
-  - Scale/threshold based per-channel activation binarization
 - [Sparsity](./compression_algorithms/Sparsity.md)
   - Magnitude sparsity
   - Regularization-based (RB) sparsity