Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Model klasifikasi biner memprediksi hasil biner (salah satu dari dua class). Gunakan jenis model ini untuk pertanyaan ya atau tidak. Misalnya, Anda mungkin ingin membuat model klasifikasi biner untuk memprediksi apakah pelanggan akan membeli langganan. Umumnya, masalah
klasifikasi biner membutuhkan lebih sedikit data dibandingkan jenis model lainnya.
Model klasifikasi kelas jamak memprediksi satu class dari tiga class atau lebih yang terpisah.
Gunakan jenis model ini untuk kategorisasi. Misalnya, sebagai retailer, Anda mungkin ingin membuat model klasifikasi kelas jamak untuk mengelompokkan pelanggan ke dalam berbagai persona.
Model regresi memprediksi nilai berkelanjutan. Misalnya, sebagai retailer, Anda mungkin ingin membuat model regresi untuk memprediksi jumlah yang akan dibelanjakan pelanggan bulan depan.
Alur kerja untuk membuat model klasifikasi atau regresi dan membuat inferensi
Proses untuk membuat model klasifikasi atau regresi di
Vertex AI adalah sebagai berikut:
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],[],[],[],null,["# Classification and regression overview\n\n**Binary classification** models predict a binary outcome (one of\ntwo classes). Use this model type for yes or no questions. For example, you might want\nto build a binary classification model to predict whether a customer would\nbuy a subscription. Generally, a binary classification\nproblem requires less data than other model types.\n\n\n**Multi-class classification** models predict one class from three\nor more discrete classes. Use this model type for categorization. For example, as a\nretailer, you might want to build a multi-class classification model to segment\ncustomers into different personas.\n\n\n**Regression** models predict a continuous value. For example, as a retailer,\nyou might want to build a regression model to predict how much a\ncustomer will spend next month.\n\nWorkflow for creating a classification or regression model and making inferences\n--------------------------------------------------------------------------------\n\nThe process for creating a classification or regression model in\nVertex AI is as follows:\n\n| To see an example of how to create, train, and use an AutoML\n| classification model for online predictions,\n| run the \"AutoML tabular training and prediction\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl-tabular-classification.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fautoml-tabular-classification.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fautoml-tabular-classification.ipynb)\n|\n|\n| \\|\n|\n[View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/automl-tabular-classification.ipynb) \n| To see an example of how to create, train, and use an AutoML\n| regression model for batch predictions,\n| run the \"AutoML training tabular regression model for batch prediction using BigQuery\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_batch_bq.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fsdk_automl_tabular_regression_batch_bq.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fsdk_automl_tabular_regression_batch_bq.ipynb)\n|\n|\n| \\|\n|\n[View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_batch_bq.ipynb) \n| To see an example of how to create, train, and use an AutoML\n| regression model for online predictions,\n| run the \"AutoML training tabular regression model for online prediction using BigQuery\" notebook in one of the following\n| environments:\n|\n| [Open in Colab](https://colab.research.google.com/github/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_online_bq.ipynb)\n|\n|\n| \\|\n|\n| [Open in Colab Enterprise](https://console.cloud.google.com/vertex-ai/colab/import/https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fsdk_automl_tabular_regression_online_bq.ipynb)\n|\n|\n| \\|\n|\n| [Open\n| in Vertex AI Workbench](https://console.cloud.google.com/vertex-ai/workbench/deploy-notebook?download_url=https%3A%2F%2Fraw.githubusercontent.com%2FGoogleCloudPlatform%2Fvertex-ai-samples%2Fmain%2Fnotebooks%2Fofficial%2Fautoml%2Fsdk_automl_tabular_regression_online_bq.ipynb)\n|\n|\n| \\|\n|\n| [View on GitHub](https://github.com/GoogleCloudPlatform/vertex-ai-samples/blob/main/notebooks/official/automl/sdk_automl_tabular_regression_online_bq.ipynb)"]]
