CLI --ignore-cols ignored on MacOS

**System Information (please complete the following information):**
- OS & Version: MacOS 12.6
- ML.NET Version: mlnet-osx-x64 - 16.13.9
- .NET Version: .NET 6.0.302

**Describe the bug**
When using the CLI from terminal to train a model using data from a csv file and specifying columns to ignore using `--ignore-cols 1, 2, 3` results in an output model and sample project that does in fact use the columns intended to be ignored as inputs for classification predictions.

**To Reproduce**
Steps to reproduce the behavior:
1. create a multi-column csv for text classification and call it `data.csv`. Include columns you don't with to be used in the predictions at all. (fill it with some meaningful data to train classification models.)
2. open a terminal and navigate to the folder containing the csv.
3. `mlnet classification --dataset "data.csv" --has-header true --train-time 10 --label-col 8 --ignore-cols 1, 2, 3, 4, 5, 6, 7, 9`
(obviously this step should include the appropriate label column (0 indexed) and ignore columns (also 0 indexed))

**Expected behavior**
Generated model and sample project should not use columns listed in the `--ignore-cols` flag arguments.

**Actual behavior**
Each of the ignored columns are still used.

Riproduci il problema su MacOS 12.6 con il comando `mlnet classification` fornito e un CSV con più colonne. Ispeziona il modello generato e il progetto di esempio per verificare che le colonne elencate in `--ignore-cols` siano escluse dagli input della classificazione.

Scritto dal modello di indicizzazione a partire dal testo della issue.