alphaolomi / highschool-dropout-prediction

highschool-dropout-prediction

highschool-dropout-prediction

highschool-dropout-prediction's Issues

Execute the 'train_predict' function for each classifier and each training set s...

highschool-dropout-prediction/student_intervention.ipynb

Lines 577 to 582 in 754e129

	"# TODO: Execute the 'train_predict' function for each classifier and each training set size\n",
	"# train_predict(clf, X_train, y_train, X_test, y_test)\n",
	"\n",
	"classifiers = [clf_A, clf_B, clf_C]\n",
	"training_subsets = [(X_train_100, y_train_100), (X_train_200, y_train_200), \n",
	" (X_train_300, y_train_300)]\n",

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This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Import any additional functionality you may need here\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 293 to 298 in 754e129

	"# TODO: Import any additional functionality you may need here\n",
	"from sklearn.cross_validation import train_test_split\n",
	"\n",
	"# TODO: Set the number of training points\n",
	"num_train = 300\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Calculate number of features\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 110 to 115 in 754e129

	"# TODO: Calculate number of features\n",
	"n_features = student_data.shape[1] - 1\n",
	"\n",
	"# TODO: Calculate passing students\n",
	"n_passed = len(student_data[student_data.passed == \"yes\"])\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Perform grid search on the classifier using the f1_scorer as the scoring method\...

highschool-dropout-prediction/student_intervention.ipynb

Lines 738 to 743 in 754e129

	"# TODO: Perform grid search on the classifier using the f1_scorer as the scoring method\n",
	"grid_obj = GridSearchCV(clf, parameters, scoring=f1_scorer)\n",
	"grid_obj_dt = GridSearchCV(clf_dt, parameters_dt, scoring=f1_scorer)\n",
	"\n",
	"# TODO: Fit the grid search object to the training data and find the optimal parameters\n",
	"grid_obj = grid_obj.fit(X_train, y_train)\n",

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This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

'` statement. Please be sure to read the instructions carefully!\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 16 to 21 in 754e129

	"Welcome to the second project of the Machine Learning Engineer Nanodegree! In this notebook, some template code has already been provided for you, and it will be your job to implement the additional functionality necessary to successfully complete this project. Sections that begin with **'Implementation'** in the header indicate that the following block of code will require additional functionality which you must provide. Instructions will be provided for each section and the specifics of the implementation are marked in the code block with a `'TODO'` statement. Please be sure to read the instructions carefully!\n",
	"\n",
	"In addition to implementing code, there will be questions that you must answer which relate to the project and your implementation. Each section where you will answer a question is preceded by a **'Question X'** header. Carefully read each question and provide thorough answers in the following text boxes that begin with **'Answer:'**. Your project submission will be evaluated based on your answers to each of the questions and the implementation you provide. \n",
	"\n",
	">**Note:** Code and Markdown cells can be executed using the **Shift + Enter** keyboard shortcut. In addition, Markdown cells can be edited by typically double-clicking the cell to enter edit mode."
	]

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Calculate number of students\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 107 to 112 in 754e129

	"# TODO: Calculate number of students\n",
	"n_students = student_data.shape[0]\n",
	"\n",
	"# TODO: Calculate number of features\n",
	"n_features = student_data.shape[1] - 1\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Initialize the three models\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 562 to 567 in 754e129

	"# TODO: Initialize the three models\n",
	"clf_A = DecisionTreeClassifier(random_state=0)\n",
	"clf_B = svm.SVC(random_state=0)\n",
	"clf_C = GaussianNB()\n",
	"\n",
	"# TODO: Set up the training set sizes\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Calculate graduation rate\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 119 to 124 in 754e129

	"# TODO: Calculate graduation rate\n",
	"grad_rate = n_passed * 100.0 / n_students\n",
	"\n",
	"# Print the results\n",
	"print \"Total number of students: {}\".format(n_students)\n",
	"print \"Number of features: {}\".format(n_features)\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Calculate failing students\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 116 to 121 in 754e129

	"# TODO: Calculate failing students\n",
	"n_failed = len(student_data[student_data.passed == \"no\"])\n",
	"\n",
	"# TODO: Calculate graduation rate\n",
	"grad_rate = n_passed * 100.0 / n_students\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Fit the grid search object to the training data and find the optimal parameters\...

highschool-dropout-prediction/student_intervention.ipynb

Lines 742 to 747 in 754e129

	"# TODO: Fit the grid search object to the training data and find the optimal parameters\n",
	"grid_obj = grid_obj.fit(X_train, y_train)\n",
	"grid_obj_dt = grid_obj_dt.fit(X_train, y_train)\n",
	"\n",
	"\n",
	"print grid_obj_dt.best_params_\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Set up the training set sizes\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 567 to 572 in 754e129

	"# TODO: Set up the training set sizes\n",
	"X_train_100 = X_train[0:100]\n",
	"y_train_100 = y_train[0:100]\n",
	"\n",
	"X_train_200 = X_train[0:200]\n",
	"y_train_200 = y_train[0:200]\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Initialize the classifier\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 731 to 736 in 754e129

	"# TODO: Initialize the classifier\n",
	"clf = GaussianNB()\n",
	"clf_dt = DecisionTreeClassifier()\n",
	"\n",
	"# TODO: Make an f1 scoring function using 'make_scorer' \n",
	"f1_scorer = make_scorer(f1_score, pos_label='yes')\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Make an f1 scoring function using 'make_scorer' \n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 735 to 740 in 754e129

	"# TODO: Make an f1 scoring function using 'make_scorer' \n",
	"f1_scorer = make_scorer(f1_score, pos_label='yes')\n",
	"\n",
	"# TODO: Perform grid search on the classifier using the f1_scorer as the scoring method\n",
	"grid_obj = GridSearchCV(clf, parameters, scoring=f1_scorer)\n",
	"grid_obj_dt = GridSearchCV(clf_dt, parameters_dt, scoring=f1_scorer)\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Create the parameters list you wish to tune\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 725 to 730 in 754e129

	"# TODO: Create the parameters list you wish to tune\n",
	"parameters = {}\n",
	"parameters_dt = {'min_samples_split':(2,3,4,5,6,7,8,9,10, 11, 12), \n",
	" 'max_depth' :(1,2,3,4,5,6,7,8,9,10),\n",
	" 'splitter': ('best', 'random')}\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Calculate passing students\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 113 to 118 in 754e129

	"# TODO: Calculate passing students\n",
	"n_passed = len(student_data[student_data.passed == \"yes\"])\n",
	"\n",
	"# TODO: Calculate failing students\n",
	"n_failed = len(student_data[student_data.passed == \"no\"])\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Shuffle and split the dataset into the number of training and testing points abo...

highschool-dropout-prediction/student_intervention.ipynb

Lines 302 to 307 in 754e129

	"# TODO: Shuffle and split the dataset into the number of training and testing points above\n",
	"X_train, X_test, y_train, y_test = train_test_split(\n",
	" X_all, y_all, stratify=y_all, test_size=95, random_state=0)\n",
	"\n",
	"# Show the results of the split\n",
	"print \"Training set has {} samples.\".format(X_train.shape[0])\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.

Set the number of training points\n",

highschool-dropout-prediction/student_intervention.ipynb

Lines 296 to 301 in 754e129

	"# TODO: Set the number of training points\n",
	"num_train = 300\n",
	"\n",
	"# Set the number of testing points\n",
	"num_test = X_all.shape[0] - num_train\n",
	"\n",

---

This issue was generated by todo based on a TODO comment in 754e129. It's been assigned to @alphaolomi because they committed the code.