#ml #analysis #eda #manipulation #string

bin+lib simple_ml

Functions required for data analysis and machine learning tasks

22 releases

✓ Uses Rust 2018 edition

0.3.1 Jul 2, 2020
0.3.0 Jun 28, 2020
0.2.11 Jun 27, 2020
0.1.14 Jun 5, 2020
0.1.12 May 31, 2020

#15 in Machine learning

Download history 145/week @ 2020-05-24 93/week @ 2020-05-31 88/week @ 2020-06-07 77/week @ 2020-06-14 91/week @ 2020-06-21 72/week @ 2020-06-28

174 downloads per month

MIT license

400KB
6.5K SLoC

Description

  • To make a library of functions that are frequently used for data anlaysis and machine learning tasks
  • Inspired by Python libraires like numpy, sklearn, pandas etc..

Changes in this version

Section Added Fixed Removed
lib_ml SSVM float_randomized (randomizing was missing), read_csv (shows the correct number of rows now), confuse_me (now takes in class values instead of fixed class )
lib_ts best_fit_line, pacf
lib_matrix head (made syntax easy), tail (made syntax easy)

Comparision with Scikit learn's output

  • OLS
  • BLR
  • SSVM
  • KNN
  • Kmeans

Vibliography ?

List of Functions and Structs

lib_matrix

1. MatrixDeterminantF : 
    > determinant_f
        x determinant_2
        x determinant_3plus
    > is_square_matrix
        x round_off_f
    > inverse_f
        x identity_matrix
        x zero_matrix

2. DataFrame:
    > describe
    > groupby

3. DataMap:
    > describe
    > groupby

1. dot_product
2. element_wise_operation
3. matrix_multiplication
4. pad_with_zero
5. print_a_matrix
6. shape_changer
7. transpose
8. vector_addition
9. make_matrix_float
10. make_vector_float
11. round_off_f
12. unique_values
13. value_counts
14. is_numerical
15. min_max_f
16. type_of
17. element_wise_matrix_operation
18. matrix_vector_product_f
19. split_vector
20. split_vector_at
21. join_matrix
22. make_matrix_string_literal
23. head
24. tail
25. row_to_columns_conversion
26. columns_to_rows_conversion

lib_ml

1. OLS:
    > fit
2. BLR:
    > fit
    > sigmoid
    > log_loss
    > gradient_descent
    > change_in_loss
    > predict
3. KNN
    > fit
    x predict
4. Distance
    > distance_euclidean
    > distance_manhattan
    > distance_cosine
    > distance_chebyshev
5. Kmeans
    > fit
6. SSVM
    > fit
    x sgd
    x compute_cost
    x calculate_cost_gradient
    x predict

1. coefficient
2. convert_and_impute
3. covariance
4. impute_string
5. mean
6. read_csv
7. root_mean_square
8. simple_linear_regression_prediction
9. variance
10. convert_string_categorical 
11. normalize_vector_f
12. logistic_function_f
13. log_gradient_f 
14. logistic_predict 
15. randomize_vector
16. randomize
17. train_test_split_vector_f
18. train_test_split_f
19. correlation
20. std_dev
21. spearman_rank
22. how_many_and_where_vector
23. how_many_and_where
24. z_score
25. one_hot_encoding
26. shape
27. rmse
28. mse
29. mae
30. r_square
31. mape
32. drop_column
33. preprocess_train_test_split
34. standardize_vector_f
35. min_max_scaler
36. float_randomize
37. confuse_me
38. cv
39. z_outlier_f
40. percentile_f
41. quartile_f

lib_nn

1. LayerDetails :
    > create_weights
    > create_bias
    > output_of_layer

1. activation_leaky_relu
2. activation_relu
3. activation_sigmoid
4. activation_tanh

lib_string

1. StringToMatch :
    > compare_percentage
        x calculate
    > clean_string
        x char_vector
    > compare_chars
    > compare_position
    > fuzzy_subset
        x n_gram
    > split_alpha_numericals
    > char_count
    > frequent_char
    > char_replace

1. extract_vowels_consonants
2. sentence_case
3. remove_stop_words
4. tokenize

lib_ts

1. acf
2. simple_ma
3. exp_ma
4. best_fit_line
5. pacf

About the author

Dependencies

~315–435KB